Electric Vehicle with MATLAB and Simulink Resources

This repository is a collection of MATLAB® and Simulink® resources for students, educators, and researchers interested in electric vehicles and related systems and subsystems. Similar extended resource collections are available for complex and engineered systems such as UAV and Renewable Energy Systems.

MathWorks® provide various tools to facilitate the design and development of electric vehicles. The diagram below highlights tools for electric vehicle and automotive design. You can find the full set of MathWorks toolboxes and blocksets at the MathWorks product page.

To help find related materials, the content is categorized based on their overall focus on related topics to EV design and development.

• Full System
• Powertrain - Electric Motor and Transmission
• Energy - Battery
• Energy - Fuel Cell
• Electronics
• Thermal
• Vehicle Dynamics
• Optimization and Efficiency
• Advanced Driver Assistance and Automated Driving Systems (ADAS/ADS)
• Model-Based Systems Engineering (MBSE)

Note: Recently added items are identified with a " ⭐ (New! 20xx-xx)" at the beginning of the line.

Full System

Highlights

• MATLAB and Simulink for Electric Vehicle Development [Content Collection] — MATLAB, Simulink, and Simscape enable engineers to model, simulate, and optimize electric vehicle systems including batteries, motors, and controllers using pre-built reference applications.
• Upskill for the Electric Vehicle Transition [Content Collection] — A curated set of free tutorials and courses to build skills in EV system development, covering motor control, battery management, fuel cells, and simulation.
• Battery Electric Vehicle Model in Simscape [Code/Model] — A modular and multi-fidelity BEV model for longitudinal powertrain analysis and drive cycle simulation using Simscape, suitable for performance and thermal efficiency studies.
• Get Started with the Virtual Vehicle Composer [Doc] — A guided app for configuring, building, and testing virtual vehicles for system-level performance analysis, including fuel economy, battery SOC, and HIL testing.

Educational and Training

• ⭐(New! 2026-04) Electrified Systems Design Engineer Professional Certificate [Online Course] — A MathWorks‑led Coursera Professional Certificate that builds job‑ready skills to model, simulate, and design complete electrified systems—integrating motors, power electronics, and batteries—using Simulink and model‑based design workflows.
• Online Courses - Automotive [Online Course] — Offers self-paced courses for automotive engineers covering Simulink fundamentals, Stateflow, and MATLAB applications for system modeling and control.
• ChalmersX: Electric and Conventional Vehicles [Online Course] — Teaches how electric and conventional powertrains work and how to analyze their performance and energy consumption.
• ChalmersX: Hybrid Vehicles [Online Course] — Focuses on designing hybrid powertrains by combining electric motors and combustion engines to meet modern vehicle requirements.
• Simscape Onramp [Online Course] — A free, interactive course introducing Simscape for modeling dynamic systems across physical domains using a physical network approach.
• Building Your Virtual Vehicle with Simulink [Content Collection] — Demonstrates how to build and simulate virtual vehicles using Simulink for use cases like thermal analysis and autonomous driving.
• Powertrain Reference Applications [Doc, Content Collection] — Provides fully assembled models of internal combustion, hybrid, and electric powertrains for simulation, calibration, and HIL testing.

Examples and Demos

• Simscape Vehicle Templates [Code/Model, Content Collection] — Provides customizable vehicle models and modular components for simulating conventional, hybrid, battery electric, and fuel cell vehicles, including suspension, braking, and ADAS systems.
• Vehicle Scenarios [Code/Model, Content Collection] — Enables simulation of vehicle maneuvers and drive cycles in a 3D Unreal Engine environment for testing perception, control, and planning algorithms.
• Electric Vehicle Powered by Brushless Direct Current (BLDC) Motor [Code/Model] — Contains open- and closed-loop models of electric all-terrain vehicles powered by BLDC motors, designed for student competitions and parameter optimization.
• Battery Electric Vehicle with Motor Cooling in Simscape [Code/Model] — Simulates a BEV with a liquid-cooled motor to evaluate thermal performance during driving maneuvers and component sizing.
• Electric Vehicle Design with Simscape [Code/Model] — Offers a comprehensive BEV model for range estimation, battery sizing, gear ratio selection, and thermal analysis using Simscape libraries.
• Hybrid (Multimode/input power-split/P0–P4), Full Electric, Fuel Cell Electric Vehicle Reference Application Projects and model [Doc] — Includes reference applications for simulating hybrid, electric, and fuel cell vehicles with various architectures and control strategies.
• Hybrid-Electric Vehicle Model in Simulink [Code/Model] — A configurable HEV model using Simscape Electrical and Driveline for system-level testing and power quality analysis.

Technical Articles and Presentations

• ⭐(New! 2026-03) Evolving Legacy Modeling Tools with the VERDE Toolchain at GM [Technical Article] — General Motors modernized vehicle energy modeling with the VERDE toolchain built on MATLAB and Simulink to enable scalable, high‑fidelity, cross‑domain simulation and optimization for next‑generation vehicle development
• ⭐(New! 2025-11) Driving the Future: Equipping Tomorrow's Engineers for the EV Revolution [Video] — Academic institutions can prepare the next generation of engineers for the electric vehicle revolution by integrating industry‑aligned EV concepts and Model‑Based Design workflows into curricula using MATLAB and Simulink.
• ⭐(New! 2025-11) From Classroom to Racetrack: How Students Engineered a Winning Electric Vehicle [Video] — DynamiΣ PRC (Formula Student team at Politecnico di Milano) used Model‑Based Design with MATLAB, Simulink, and Simscape to virtually prototype, optimize, and deploy an electric race car, translating classroom theory into a competition‑winning vehicle.
• ⭐(New! 2025-10) Optimizing EV Battery System Performance with Model-Based Design [Technical Article] — Formula SAE teams use Model-Based Design with MATLAB, Simulink, and Simscape to model, simulate, and optimize electric vehicle systems—particularly battery management and thermal performance—to improve race performance and competition results.
• ⭐(New! 2025-10) Accelerating Vehicle Development with Virtual Vehicles [Video] — Virtual vehicle models built with MATLAB and Simulink enable early system‑level simulation, risk reduction, and scalable validation to accelerate automotive development while minimizing reliance on costly physical prototypes.
• ⭐(New! 2025-09) General Motors Cuts Testing Time in Half by Simulating E-Drive System [Video] — General Motors uses virtual ECUs and software‑in‑the‑loop simulation with MATLAB, Simulink, and Simscape to accelerate automotive testing by enabling high‑fidelity virtual calibration and significantly reducing reliance on physical hardware.
• Speed-up Software-Defined Vehicle Development [Content Collection] — Explores how Model-Based Design supports the development of software-defined vehicles by enabling modular architectures, early validation, and reuse across ECUs, zonal controllers, and HPC platforms.
• Adaptive Design of Experiment for Simultaneous Modeling and Optimization with Artificial Intelligence – Ford [Presentation] — Demonstrates how AI-powered surrogate modeling and adaptive design of experiments can accelerate vehicle design optimization by replacing costly simulations with fast predictive models.
• Building a Hybrid Electric Vehicle Prototype System for Processor-in-the-Loop Simulations – NXP Semiconductors [Technical Article] — Describes how NXP used Simulink and Powertrain Blockset to develop a hybrid electric vehicle prototype and run processor-in-the-loop simulations on the GreenBox II platform.
• Building Virtual Vehicle Models for Large-Scale, Cloud-Based Simulations [Technical Article] — Details a workflow using the Virtual Vehicle Composer app to build, customize, and deploy vehicle models for large-scale cloud simulations and performance testing.
• Top 7 Use Cases for Electric Vehicle Simulation [Technical Article] — Highlights common EV simulation tasks including powertrain architecture exploration, regenerative braking tuning, suspension design, ADAS validation, and hardware-in-the-loop testing.

Applications

• ⭐(New! 2026-04) Monarch Tractor uses Simulink TTControl integration [Industry Example] — Monarch Tractor used Simulink with TTControl TTC580 production ECU modules to design a driver-optional, smart and 100% electric tractor.
• ⭐(New! 2025-09) Designing India's First High-Voltage Electric Motorcycle with Model-Based Design [Industry Example] — Raptee.HV uses Model‑Based Design with MATLAB, Simulink, and code generation to rapidly design, validate, and deploy India's first high‑voltage electric motorcycle, accelerating development while meeting performance, efficiency, and charging‑infrastructure goals.
• How Simulation Accelerates Vehicle Electrification [Video] — Explains how simulation tools like MATLAB, Simulink, and Simscape help engineers design and validate electric vehicle systems efficiently.
• General Motors Cuts Testing Time in Half by Simulating E-Drive System [Industry Example] — GM used virtual ECUs and plant models to achieve 95% calibration targets before hardware availability, significantly reducing physical testing time.
• Ather Energy Develops Electric Two-Wheeled Scooter and Charging Stations Using Model-Based Design [Industry Example] — Ather Energy used simulation to evaluate design alternatives and optimize control software for their electric scooter and charging stations.
• Bosch and National Institute of Technology Calicut Collaborate on EV Course to Prepare Students for Industry [Industry Example] — Bosch and NIT Calicut created a hands-on EV systems engineering course to bridge the gap between academic learning and industry needs.
• Bosch eBike Systems Develops Electric Bike Controller with Model-Based Design [Industry Example] — Bosch developed an eBike controller using Simulink and Embedded Coder, enabling rapid prototyping and compliance with safety standards.
• University of Waterloo Develops Award-Winning Fuel Cell Technology Using Model-Based Design [Industry Example] — Waterloo's student team used Simulink to design a fuel-cell-powered vehicle, winning top honors in a national competition.
• Autonomous Electric Tractor Brings Artificial Intelligence to the Field [Industry Example] — Monarch Tractor built a fully autonomous electric tractor using AI and Simulink, helping reduce emissions and improve farming efficiency.
• RC Cars, VR, and Haptic Feedback Transform Automotive Engineering [Industry Example] — Students at HAW Hamburg use programmable RC cars, VR, and haptic feedback to simulate and test automotive algorithms in a lab setting.

Powertrain - Electric Motor and Transmission

Highlights

• MATLAB and Simulink for Motor Drives and Traction Motors [Content Collection] — Provides tools to model, simulate, and implement motor control algorithms for traction motors, including fault detection, autotuning, and hardware-in-the-loop testing.
• Motor Control Design with Simulink [Content Collection] — Demonstrates how to design field-oriented control systems in Simulink, including PI controller tuning and flux weakening strategies.
• How to Design Motor Controllers Using Simscape Electrical [Video Series] — Explains how to model BLDC motors, simulate back-EMF, and design speed controllers using Simscape Electrical.
• What Is Field-Oriented Control? [Content Collection] — Describes the principles and implementation of field-oriented control for PMSM and BLDC motors, including transformations and modulation techniques.
• What Is BLDC Motor Control? [Content Collection] — Covers trapezoidal and field-oriented control methods for BLDC motors, with modeling, tuning, and code generation workflows.
• What Is Motor Modeling and Simulation? [Content Collection] — Discusses different fidelity levels of motor models for system design, control development, and traction applications.
• Powertrain Blockset [Content Collection] — Offers preassembled reference models for gasoline, hybrid, and electric powertrains, with tools for component sizing, calibration, and HIL testing.
• Developing Virtual Vehicles Using Powertrain Blockset [Presentation] — Shows how to build and parameterize virtual vehicle models using benchmarking data and validate them against real-world measurements.

Educational and Training

• Introduction to Motor Control [Online Course] — Leran how to model electric motors and inverters and design controllers using Voltage-by-Frequency and Field-Oriented Control methods in Simulink.
• ⭐(New! 2025-09) Motor Modeling with Simscape Electrical [Online Course] — Learn to create a lumped-parameter model of an electric motor using Simscape Electrical and connect it to a closed-loop controller built using Motor Control Blockset. Then, incorporate finite element data and loss modeling to increase the model fidelity.
• ⭐(New! 2026-04) Motor Control Algorithms with Simulink and Simscape Learning Path [Online Course] — Self-paced Learning Path that teaches how to model, design, and tune motor control algorithms—such as field-oriented control for permanent magnet synchronous motors—using Simulink, Simscape Electrical, and Motor Control Blockset.
• ⭐(New! 2026-04) Control Techniques for PMSM [Online Course] — Self-paced course that explains and compares advanced control techniques for permanent magnet synchronous motors, including field-oriented control and related strategies, using Simulink and motor drive models.
• Transfer Function Analysis of Dynamic Systems [Course Module] — Offers interactive lessons and MATLAB apps to teach Laplace transforms, pole-zero analysis, and frequency domain analysis for dynamic systems.
• Virtual Hardware and Labs for Controls [Course Module] — Provides virtual labs and mechanisms for studying control systems, enabling students to simulate and test controllers in Simulink.
• Interactive Live Script Control Tutorials for MATLAB and Simulink [Course Module] — Features interactive tutorials for modeling, analyzing, and designing control systems using MATLAB Live Scripts.
• Introduction to Brushless DC Motor Control [Technical Article] — Explains the fundamentals of BLDC motors, including commutation techniques, torque generation, and simulation methods.
• Understanding BLDC Motor Control Algorithms [Technical Article] — Describes the components of BLDC motor control algorithms and how to simulate motor behavior using MATLAB and Simulink.
• Estimate PMSM Parameters Using Custom Hardware [Doc] — Provides a workflow for estimating PMSM parameters using custom motor-control hardware and Embedded Coder.
• Motor Control with TI LaunchPad [Doc] — Demonstrates closed-loop Field-Oriented Control of PMSM using TI LaunchPad and Simulink models.
• Six-Step Commutation of BLDC Motor Using Sensor Feedback [Doc] — Implements six-step commutation to control speed and direction of BLDC motors using Hall sensor or encoder feedback.
• Hall Sensor Sequence Calibration of BLDC Motor [Doc] — Calculates the Hall sensor sequence for BLDC motors in open-loop control to support six-step commutation.

Examples and Demos

• ⭐(New! 2026-04) Simulate PMSM Parameter Estimations [Doc] — Use Motor Control Blockset library blocks in Simulink to simulate and validate permanent magnet synchronous motor parameter estimation algorithms for accurate motor modeling and control design.
• ⭐(New! 2026-04) Field-oriented Control of PMSM with Six-Step Transition [Doc] — Implement field‑oriented control of a permanent magnet synchronous motor with a seamless transition into six‑step operation to extend high‑speed performance without increasing inverter DC bus voltage.
• Import a Motor-CAD Thermal Model into Simulink and Simscape [Code/Model] — Demonstrates how to import a Motor-CAD model and generate a reduced-order thermal model for use in Simscape to simulate motor temperature under dynamic conditions.
• Motor Efficiency Improvements With Tuned Control Parameters [Code/Model] — Uses optimized field-oriented control to reduce motor losses in a PMSM drive, including scripts for controller tuning and frequency response analysis.
• Motor Control Blockset – Examples [Doc, Content Collection] — Provides reference examples for developing and testing motor control algorithms using Simulink, including FOC, six-step commutation, and sensorless control.
• Dual Motor Control with TI LaunchPad [Code/Model] — Implements closed-loop field-oriented control for two PMSMs using TI's F28069M LaunchPad and DRV8301 inverters.
• BLDC Hysteresis Current Control [Doc] — Shows how to implement hysteresis-based current control for a BLDC motor using a three-phase inverter and Simscape Electrical.
• BLDC Motor Speed Control with Cascade PI Controllers [Doc] — Demonstrates a cascade control structure with autotuned PI controllers for regulating BLDC motor speed and DC link voltage.
• BLDC Position Control [Doc] — Implements a cascade control system for BLDC motor position using PI controllers for position, speed, and current loops.
• Parallel Hybrid Transmission [Doc] — Simulates a parallel hybrid architecture where electric and combustion power are applied in parallel to the drivetrain.
• Series Hybrid Transmission [Doc] — Models a series hybrid system where engine power is converted to electricity and used to drive the vehicle via an electric motor.
• Power-Split Hybrid Transmission [Doc] — Demonstrates a hybrid architecture using a planetary gear to split power between engine and electric motor for variable gear ratios.
• Two Mode Hybrid Transmission [Doc] — Simulates a two-mode hybrid system with multiple gear ratios and power-split modes for efficient operation across driving conditions.
• Hybrid (Multimode/input power-split/P0-P4) Vehicle Reference Application Projects and model [Doc] — Provides reference models for simulating various hybrid and electric vehicle architectures including multimode and power-split configurations.
• Hybrid-Electric Vehicle Model in Simulink [Code/Model] — Offers a configurable Simulink model of a hybrid-electric vehicle using Simscape for system-level and detailed analysis.

Technical Articles and Presentations

• Combining Model-Based Systems Engineering and Model-Based Design to Accelerate Electric Drivetrain Development [Technical Article] — Describes a workflow integrating System Composer, Simulink, and Simscape to enable early validation, traceability, and reuse across electric drivetrain development, including HIL testing and CI automation.
• Designing a Torque Controller for a PMSM through Simulation on a Virtual Dynamometer [Technical Article] — Explains how to use FEA-based motor models and virtual dynamometers in Simulink to design torque controllers for PMSMs, reducing hardware testing and improving control accuracy.
• Beyond PID: Exploring Alternative Control Strategies for Field-Oriented Controllers [Technical Article] — Introduces advanced control methods like active disturbance rejection, model predictive control, and reinforcement learning for field-oriented motor control beyond traditional PID.
• Master Class: Fulfill Range, Acceleration, and Cost Targets Using Battery Sizing [Presentation] — Demonstrates how to use vehicle models and drive cycles to optimize battery pack topology and cell count for meeting range, acceleration, and cost targets.
• Field-Weakening Control for PMSMs with Simulink and Motor Control Blockset [Presentation] — Shows how to implement and calibrate field-weakening control algorithms for PMSMs using Simulink and Motor Control Blockset, including code deployment to embedded hardware.
• How to Use Rapid Control Prototyping to Validate Electric Motors and Power Converters [Presentation] — Explains how to use Simulink Real-Time and Speedgoat hardware for rapid control prototyping of motor and converter control algorithms before final deployment.
• Simulate, Design, and Test Field-Weakening Control Design with Simulink [Presentation] — Covers two workflows for field-weakening control design: one using linear models and another using high-fidelity FEA-based PMSM models for embedded code generation.
• Simulating Torque Ripple for Motor Control System Design [Presentation] — Highlights the importance of torque ripple in motor drives and shows how to use FEA data in Simscape Electrical to model and mitigate ripple effects.
• Dual Motor DHT Modeling and Simulation – PATAK [Presentation] — Describes the modeling and simulation of dual-motor hybrid transmissions using MATLAB and Simulink, focusing on energy management, mode switching, and control optimization.

Applications

• SynRMs Could Change the Electric Vehicle Game [Industry Example] — Researchers developed control strategies for synchronous reluctance motors (SynRMs), offering a sustainable alternative to rare-earth magnet motors in EVs by reducing cost and environmental impact.
• ATB Technologies Cuts Electric Motor Controller Development Time by 50% Using Code Generation for TI's C2000 MCU [Industry Example] — ATB Technologies used Model-Based Design and automatic code generation to develop high-performance motor controllers, cutting development time in half and improving software quality.
• PATAC Automates Digital Engine Research Framework to Improve Efficiency [Industry Example] — PATAC created an intelligent framework using MATLAB tools to automate engine design, enabling rapid updates and optimal decision-making for electric vehicle powertrains.
• LG Electronics Develops ISO 26262–Compliant Power Inverter Control Software with Model-Based Design [Industry Example] — LG Electronics used MATLAB and Simulink to develop and verify inverter control software that meets ISO 26262 and AUTOSAR standards, improving communication and reducing verification time.

Energy - Battery

Highlights

• MATLAB and Simulink for Battery Systems [Content Collection] — Provides tools for modeling battery cells and packs, designing battery management systems, and simulating thermal and electrical behavior under various operating conditions.
• What Is Battery Modeling? [Content Collection] — Explains how battery models are used for characterization, SOC/SOH estimation, algorithm development, and real-time simulation, with a focus on equivalent circuit models.
• Battery Pack Modeling [Doc, Content Collection] — Offers a workflow for designing battery packs using Simscape Battery, including cell configuration, thermal modeling, and integration with BMS and cooling systems.
• Simscape Battery Essentials [Video Series, Content Collection] — A video series that teaches how to build, parameterize, and simulate battery modules and packs, including SOC estimation, cell balancing, and thermal analysis.
• Battery Management System (BMS) [Technical Article] — Describes the role of BMS in monitoring, protecting, and optimizing battery performance, including SOC/SOH estimation, cell balancing, thermal management, and fault detection.

Educational and Training

• Simscape Battery Onramp [Online Course] — A free, self-paced course that teaches how to simulate battery packs and battery management systems using Simscape, including thermal effects and charging algorithms like CC-CV and coulomb counting.
• Battery Systems: introduction [Course Module] — Covers battery pack design, cell modeling (electrical and thermal), and BMS fundamentals using MATLAB, Simulink, and Simscape, with interactive examples and SoC estimation techniques.
• Battery Pack Modeling [Online Course] — Offers training on modeling battery packs using the Battery Builder app in Simscape, including cell-to-pack workflows, thermal modeling, and integration of cooling plates.
• ⭐(New! 2025-09) Battery State Estimation [Online Course] - Model Kalman filter-based techniques to estimate battery state using Simscape Battery. Learn to parameterize and tune the Kalman filter for battery state estimation. Estimate the state of charge, state of energy, and state of health to seek optimum performance of the battery pack.
• ⭐(New! 2026-04) Battery Management System Modeling [Online Course] — This course introduces battery management system (BMS) modeling using MATLAB, Simulink, and Simscape, focusing on concepts such as state-of-charge estimation, cell balancing, thermal behavior, and system-level simulation for designing and validating battery systems. [mathworks.com]
• Developing Battery Systems with Simulink and Simscape [Technical Article] — Explains how Simulink and Simscape Battery support battery system development, from pack design and thermal management to BMS algorithm development and hardware-in-the-loop testing.

Examples and Demos

• ⭐(New! 2025-09) Build Simple Model of Battery Pack in MATLAB and Simscape [Code/Model] — Use Simscape Battery to architect, parameterize, and assemble scalable battery pack models—from cells to modules and packs—for system‑level simulation of electrical and thermal behavior.
• ⭐(New! 2026-04) Build Battery Model from Custom Cell Component [Doc] — Battery pack modeling workflow using custom electrochemical cell components to assemble modules and packs with electrical and thermal fidelity in Simscape Battery.
• ⭐(New! 2026-04) Simulate Battery Using Doyle-Fuller-Newman Model [Doc] — High‑fidelity electrochemical battery cell simulation using the Doyle–Fuller–Newman model to capture lithium‑ion transport, reaction kinetics, voltage response, and internal states in Simscape Battery.
• ⭐(New! 2026-04) Battery Single Particle [Doc] — Single‑particle electrochemical battery cell model capturing solid‑phase lithium diffusion, voltage dynamics, and state‑of‑charge behavior with reduced computational complexity for system‑level simulation.
• ⭐(New! 2026-04) Battery P2D Modeling [Doc] — Physics‑based pseudo‑two‑dimensional (P2D) lithium‑ion battery modeling using PDE Toolbox to capture electrochemical transport, reaction kinetics, and voltage response.
• ⭐(New! 2026-04) Model Battery Performance [Doc] — Multiphysics battery performance modeling using PDE Toolbox to analyze electrochemical behavior, thermal effects, and operating conditions for physics‑based battery analysis.
• ⭐(New! 2026-04) Perform Weighted Parameter Estimation for Single-Particle Battery Model [Doc] — Weighted parameter estimation workflow using Simulink Design Optimization to calibrate single‑particle battery model parameters against experimental data with emphasis on critical operating regions.
• ⭐(New! 2026-04) Predict Battery State of Charge Using Machine Learning [Doc] — Machine‑learning‑based battery state‑of‑charge prediction using data‑driven models to improve SOC estimation accuracy under varying operating conditions.
• ⭐(New! 2026-04) Predict Battery State-Of-Charge Using Time Series Modeler App [Doc] — Battery state‑of‑charge prediction using the Time Series Modeler app with data‑driven system identification, model comparison, and validation workflows for accurate SOC estimation.
• Battery State of Charge Estimation Using Deep Learning [Doc] — End-to-end MATLAB and Simulink workflow for lithium‑ion battery state‑of‑charge estimation using deep learning, covering requirements definition, data preparation, neural network training and compression, validation, code generation, and deployment for electric vehicle battery management systems
• Explore Techniques to Estimate Battery State of Charge [Doc] — Demonstrates how to estimate battery SOC using Kalman filtering and Coulomb counting, comparing accuracy and robustness under noisy conditions.
• Battery Pack Design Solution for Battery EVs in Simscape [Code/Model] — Provides Simscape models for battery pack thermal management, SOC estimation using Kalman filters, and neural network-based temperature prediction.
• Battery Builder App [Doc] — Offers an interactive interface to design battery packs with thermal effects, visualize 3D geometry, and generate Simscape models for simulation.
• Estimate Battery Parameters Per Experiment – Coding approach [Doc] — Shows how to estimate battery model parameters using multiple experiments and MATLAB code, including voltage, resistance, and capacity.
• Estimate Battery Parameters Per Experiment – GUI approach [Doc] — Provides a graphical workflow for estimating battery parameters from charge/discharge experiments using Simulink Design Optimization.
• Battery State of Charge Workflow – Deep Learning [Doc] — Walks through a deep learning-based SOC estimation workflow including data preparation, training, integration into Simulink, and code generation.
• EV Battery Cooling System [Doc] — Simulates an EV battery cooling system using cold plates, radiators, and refrigerant loops under drive cycle and fast charge conditions.
• Parameter Tuning for Digital Twins [Doc] — Explains how to deploy battery parameter estimation workflows for digital twins using Simulink Design Optimization and Simulink Compiler.
• Reduced-Order Model for Thermal Behavior of Battery [Doc] — Uses finite element analysis and modal decomposition to generate reduced-order thermal models for battery cells during fast charging.
• Thermal Analysis for New and Aged Battery Packs [Doc] — Compares thermal performance of new and aged battery packs under constant discharge, accounting for resistance and cooling degradation.
• Protect Battery During Charge and Discharge for Electric Vehicle [Doc] — Demonstrates how to implement protection logic for battery packs during charging and discharging using Simscape Battery blocks.

Applications, Technical Articles, and Presentations

• ⭐(New! 2025-10) Model, Simulate and Analyze Faults for Battery System [Video] — Use MATLAB, Simulink, Simscape Battery, and Simulink Fault Analyzer to model battery packs, simulate electrical and thermal behavior, inject faults, and perform FMEA to validate battery management system robustness and safety.
• Exponent Energy Develops 15-Minute Fast-Charging Battery System for Electric Vehicles Using Model-Based Design [Industry Example] — Exponent Energy used Model-Based Design to rapidly develop a 400V EV battery pack and fast charger, achieving full charge in 15 minutes with minimal degradation over 3,000 cycles.
• Developing Battery Management Systems – Our Next Energy [Presentation] — Our Next Energy outlines the architecture and algorithms of their BMS, including SOC, SOP, and SOH estimation, fault diagnosis, thermal management, and system safety protocols.
• Battery Fast Charge with Simscape Battery and About:Energy [Technical Article] — Demonstrates how to generate safe fast-charge profiles using Simscape Battery and custom cell models, accounting for electrochemical dynamics, thermal effects, and pack-level constraints.

Energy - Fuel Cell

Highlights

• ⭐(New! 2025-09) MATLAB and Simulink for Fuel Cells and Electrolyzers [Content Collection] — Efficient development of fuel cell and electrolyzer applications requires simulation models of adequate fidelity. These models enable you to perform design space exploration, analyze design tradeoffs, and help inform control systems development.
• Fuel Cell Model [Content Collection] — Describes how fuel cells convert hydrogen and oxygen into electricity and water, and provides modeling tools for different levels of fidelity to support control system development, thermal analysis, and hardware-in-the-loop testing.
• Hydrogen Electrolyzer [Content Collection] — Explains how hydrogen electrolyzers split water into hydrogen and oxygen using electrical energy, and offers simulation models for electrochemical reactions, thermal management, and integration into green hydrogen systems.
• Gas Mixture Domain [Code/Model] — A custome Simscape domain designed to handle mixtures of semi-perfect gases with an example of modeling a fuel cell.

Educational and Training

• Fuel Cells: Dynamic Modeling and Control with Power Electronics Applications [Book] — Covers advanced modeling and control techniques for fuel cells and hybrid energy systems, including linear and nonlinear control, with MATLAB and Simulink examples for PEM fuel cells and hybrid renewable systems.
• Designing Fuel Cell Systems Using System-Level Design [Technical Article] — Explains how to use Simulink and Simscape to model fuel cell systems, including thermal, gas, and liquid domains, and optimize performance across design variants and operating conditions.

Examples and Demos

• ⭐(New! 2026-04) Fuel Cell Equivalent Circuit [Doc] — Fuel cell equivalent‑circuit block modeling voltage losses, dynamic response, and power behavior for system‑level fuel cell and electrified powertrain simulations.
• Fuel Cell Vehicle Model in Simscape [Code/Model, Video] — Simulates a fuel cell electric vehicle with a battery and cooling system using Simscape, allowing drive cycle testing and gas species tracking in the fuel cell domain.
• Fuel Cell–Battery Driven Electric Motor & Hydrogen Transfer [Code/Model] — Models the interaction between a fuel cell and battery supplying an electric motor, including hydrogen transfer thermodynamics and cooling regulation.
• Fuel Cell [Doc] — Provides a block-level model of a fuel cell stack with configurable fidelity, supporting simplified and detailed electrochemical modeling for simulation and control design.
• Fuel Cell System [Doc] — Simulates a complete fuel cell system operating under stoichiometric conditions, with real-time simulation capabilities and performance logging.
• Hydrogen Refueling Station [Doc] — Models a hydrogen refueling station with multi-stage compression, buffer storage, and cooling systems, following SAE J2601 protocols for safe and efficient hydrogen dispensing.
• PEM Electrolysis System [Doc] — Simulates a PEM electrolyzer that splits water into hydrogen and oxygen, including thermal and gas flow modeling, pressure regulation, and dehumidification.
• PEM Fuel Cell System [Doc] — Models a PEM fuel cell stack with detailed gas flow, thermal management, and humidification systems, supporting dynamic operation and control development.

Applications, Technical Articles, and Presentations

• Hydrogen Fuel Cells Reduce CO2 Emissions [Industry Example] — Nuvera used MATLAB and Simulink to design fuel cell engines for forklifts and container handlers, significantly reducing CO₂ emissions and enabling fast refueling and long-range operation in commercial vehicles.
• Stanford Applies Real-Time Simulation to Marry Low-Carbon Fuels with Traditional Combustion Engines [Industry Example] — Stanford researchers used Speedgoat real-time simulation and MATLAB tools to retrofit diesel engines with low-carbon fuels, achieving reduced emissions and improved performance with minimal hardware changes.
• University of Waterloo Develops Award-Winning Fuel Cell Technology Using Model-Based Design [Industry Example] — The University of Waterloo team won a national competition by designing a fuel-cell-powered vehicle using Simulink, demonstrating the feasibility and efficiency of hydrogen fuel cell systems.
• BOSCH Fuel Cell System Model Customized Based on Simscape [Presentation] — Bosch developed a detailed fuel cell system model using Simscape, integrating components like injectors, blowers, and compressors, and optimizing performance through simulation and real test data.

Electronics

Highlights

• Power Electronics Simulation [Content Collection] — Enables modeling and simulation of power converters, motor drives, and battery systems using Simulink and Simscape Electrical, supporting controller design, fault analysis, and hardware-in-the-loop testing.
• MATLAB and Simulink for Power Conversion Control [Content Collection] — Provides tools to model and simulate power conversion systems, design digital controllers, and generate production code for embedded hardware including microcontrollers and FPGAs.
• MATLAB and Simulink for Electronics Systems [Content Collection] — Supports design and simulation of signal processing, control systems, and embedded electronics, with capabilities for code generation, verification, and integration with hardware platforms.
• Power Electronics Hardware-in-the-Loop (HIL) Testing [Content Collection] — Describes how to use Simulink and Speedgoat hardware for real-time HIL testing of power electronics controllers, enabling validation before physical prototyping.
• How to Develop DC-DC Converter Control in Simulink [Video Series, Technical Article] — Demonstrates modeling and control of DC-DC converters using Simulink and Simscape Electrical, including SEPIC topology, PID tuning, efficiency mapping, and code generation for TI microcontrollers.

Educational and Training

• Introduction to Power Electronics [Course Module] — A 14-week self-paced course covering switching components, AC-DC rectifiers, DC-DC converters, DC-AC inverters, and basic control, with video lectures, quizzes, and simulation problems.
• Power Electronics Simulation Onramp [Online Course] — Teaches how to simulate power electronics converters in Simscape Electrical, including modeling buck converters at different fidelity levels and implementing closed-loop control.
• DC Circuit Analysis [Course Module] — Offers interactive MATLAB live scripts and Simscape models for mesh and nodal analysis, Thevenin circuits, RL/RLC circuits, and op-amps, including virtual oscilloscope measurements.
• Electrical Engineering Virtual Electric Machine & Power Labs [Course Module] — Provides eight virtual labs simulating three-phase systems, transformers, DC motors, synchronous machines, and generators, with lab assignments mimicking real hardware experiments.
• Circuit Simulation Onramp [Online Course] — Introduces analog circuit simulation in Simscape, covering RC/RLC circuits, op-amps, filters, and fault protection using the physical network approach.
• Power Systems Simulation Onramp [Online Course] — Guides users through simulating power systems by modeling a microgrid, measuring three-phase circuits, and evaluating control algorithms like droop control and MPPT.

Examples and Demos

• ⭐(New! 2026-04) Simscape Electrical Support Library for Power Systems [Code/Model] — Curated Simscape Electrical support library that helps power systems engineers build, convert, and simulate power system and power electronics models using native Simscape technology with reusable components and examples.
• ⭐(New! 2026-04) Model Short-Circuit Fault in EV Charging Cable [Doc] — Model and simulate a short‑circuit fault in an electric vehicle charging cable using Simscape Electrical to analyze fault currents, protection behavior, and system safety.
• ⭐(New! 2026-04) Parameterize MOSFET from Data Sheet and Create Part Collection [Doc] — Parameterize a MOSFET model directly from manufacturer datasheet values to create accurate, simulation‑ready power semiconductor models in Simscape Electrical.
• ⭐(New! 2026-04) spsConversionAssistant [Doc] — Guided utility to automatically convert legacy Specialized Power Systems models into equivalent Simscape Electrical models, preserving parameters and connections while generating a report of supported and unsupported blocks.
• Buck Converter with Thermal Dynamics [Doc] — Models a synchronous buck converter with MOSFETs and thermal ports to simulate electrical switching behavior and heat dissipation, including controller design and thermal analysis.
• Simulating Thermal Effects in Semiconductors [Doc] — Demonstrates how to simulate heat generation and temperature rise in semiconductor devices using thermal ports and Cauer or Foster thermal models.
• Estimating Transfer Function Models for a Boost Converter [Doc] — Shows how to estimate a transfer function from frequency response data using sinestream input signals and Simulink Control Design tools.
• Control Design of a Boost Converter Using Frequency Response Data [Doc] — Explains how to design a PID controller for a boost converter by estimating its frequency response and tuning gains using Simulink tools.
• Frequency Response Estimation for Power Electronics Model Using Pseudorandom Binary Signal [Doc] — Uses PRBS signals to estimate the frequency response of a boost converter, offering faster simulation and higher resolution than sinestream methods.
• Improve Simulation Speed of Power Electronics Systems with Reduced Order Modeling [Doc] — Enhances simulation speed by replacing high-fidelity switches with reduced-order models in electro-thermal DC-DC converters.
• Choose Blocks to Model Power Electronic Converters [Doc] — Model power electronic converters by balancing fidelity and complexity; use prebuilt converter blocks for common topologies and system-level tasks; and use discrete components for uncommon topologies or high-fidelity, switch-level applications.
• Three-Phase High-Power Converter Design and Analysis Workflow [Doc] — Guides the design and analysis of a three-phase converter using IGBT models, including thermal and electrical performance evaluation.
• Buck Power Train Design Workflow [Doc] — Uses the SMPS workflow to design a buck converter, including operating point analysis, compensator design, and time-domain simulation.
• Automotive Electrical System Simulation and Control [Code/Model] — Simulates a conventional vehicle electrical system with alternator, battery, loads, and idle control, supporting component sizing and system-level analysis.

Technical Articles and Presentations

• ⭐(New! 2025-12) Full-switching Electric Drive FPGA-based Hardware-in-the-Loop Simulation [Video] — Perform high‑fidelity, FPGA‑based hardware‑in‑the‑loop testing of electric motor drive and power electronics controllers using MATLAB, Simulink, HDL Coder, and real‑time hardware to accurately capture high‑frequency switching dynamics before deploying to physical systems.
• Estimating the Frequency Response of a Power Electronics Model [Technical Article] — Describes a six-step workflow for estimating the frequency response of an open-loop boost converter using Simscape Electrical and Simulink Control Design tools to derive a linear time-invariant model for controller design.
• Estimating the Frequency Response of a Power Electronic Model: Sinestream vs. Pseudo-Random Binary Sequence (PRBS) [Technical Article] — Compares sinestream and PRBS methods for frequency response estimation in buck converters, highlighting trade-offs in estimation time, frequency resolution, and accuracy.
• Cascade Digital PID Control Design for Power Electronic Converters [Technical Article] — Presents a seven-step workflow for tuning cascade PID controllers in buck converters using frequency response estimation, with inner current and outer voltage loops for improved regulation.
• Power Electronics HIL Testing Using Simscape to HDL Conversion [Video] — Explains how to convert Simscape models into HDL code for deployment on FPGA-based real-time systems, enabling high-speed hardware-in-the-loop testing of power electronics controllers.

Applications

• Unplugged: The New Way to Charge Electric Vehicles [Industry Example] — Lumen Freedom developed a wireless EV charging system for McLaren's Speedtail using resonant inductive coupling, enabling static and dynamic charging with over 92% efficiency and eliminating the need for physical connectors.
• How AMZ Racing Designed the Motor Controller to Achieve 0 to 100 km/h in 0.956 Seconds [Industry Example] — AMZ Racing used Simulink and HDL Coder to design a custom motor controller and inverter software, achieving a world record for EV acceleration with precise torque control and FPGA-based implementation.
• HS Bochum Students Design and Build a Motor Controller for an E-Longboard with Model-Based Design [Industry Example] — Students at HS Bochum built an electric longboard powered by dual BLDC motors using Model-Based Design, gaining hands-on experience with field-oriented control and embedded code generation.
• Leonardo DRS Performs FPGA-Based Hardware-in-the-Loop Testing of Shipboard Power Electronics Systems [Industry Example] — Leonardo DRS used Simulink, Simscape Electrical, and HDL Coder to simulate and test shipboard power electronics systems in real time on FPGA hardware, reducing costs and improving reliability.
• ABB Accelerates Application Control Software Development for a Power Electronic Controller [Industry Example] — ABB used Simulink and Simscape Electrical to design and automatically generate control software for the AC 800PEC controller, significantly reducing development time and improving code accuracy.

Thermal

Highlights

• Battery Thermal Management System [Content Collection] — Explains how to model and simulate battery thermal management systems using MATLAB and Simulink, including active, passive, and hybrid cooling strategies, thermal path modeling, and control logic for temperature regulation.
• Battery Thermal Management System Design [Video] — Demonstrates how to model a battery thermal management system for a small EV using Simscape, diagnose control issues, and analyze energy usage under different operating conditions.
• Examples in Heat Transfer [Content Collection, Code/Model] — A GitHub repository with MATLAB-based examples for solving canonical heat transfer problems using Symbolic Math Toolbox, PDE Toolbox, and Simscape Fluids, including conduction, convection, and transient heat flow.

Educational and Training

• Thermodynamics [Course Module] — Offers interactive live scripts that teach thermodynamic principles such as energy conservation, conduction, convection, and transient heat transfer using MATLAB and Simscape.
• Battery Systems: introduction [Course Module] — Covers battery pack design, cell modeling, and battery management systems using MATLAB, Simulink, and Simscape, including SOC estimation and thermal modeling.
• Heat Conduction Through Iron Rod [Doc] — Demonstrates how to model heat conduction and convection in a rod using Simscape thermal blocks, comparing lumped and distributed thermal mass models.
• Heat Transfer in a Thermal Liquid Pipe [Doc] — Shows how mass flow rate, pipe geometry, and environmental conditions affect heat transfer in a thermal liquid pipe using Simscape Fluids.
• Pressure Loss and Mass Flow Rate in a Thermal Liquid Pipe [Doc] — Explores how pipe friction and elevation changes impact pressure loss and flow rate, using Bernoulli's principle and Simscape simulation.
• Parameterize a Simple Heat Exchanger [Doc] — Uses the NTU method to compare heat exchanger geometries and fluids, calculating effectiveness and thermal performance in Simscape Fluids.
• EV Battery Cooling System Design [Doc] — Models a battery cooling system with cold plates, radiators, and evaporators, analyzing heat transfer and coolant behavior under different ambient conditions.

Examples and Demos

• ⭐(New! 2026-01) MATLAB Interface for REFPROP and CoolProp [Code/Model] — MATLAB interface enabling access to REFPROP and CoolProp thermophysical property libraries for high‑accuracy fluid property calculations in thermal and energy system simulations.
• ⭐(New! 2026-04) Model Battery Temperatures Using Reduced-Order Thermal Models [Doc] — Reduced‑order thermal modeling of lithium‑ion batteries to estimate cell and pack temperature dynamics efficiently for system‑level simulation and control design.
• ⭐(New! 2026-04) Model Heat Exchange Between Cells [Doc] — Inter‑cell thermal coupling workflow for modeling heat transfer paths between battery cells to improve pack‑level temperature distribution and thermal management accuracy.
• ⭐(New! 2026-04) Electric Vehicle Thermal Management With CO2 [Doc] — Electric vehicle thermal management system modeling using CO₂ refrigerant to simulate cabin conditioning, battery thermal control, and heat pump efficiency under varying operating conditions.
• ⭐(New! 2026-04) 3-D Battery Module Cooling Analysis Using Fourier Neural Operator [Doc] — 3‑D battery module cooling analysis combining physics‑based PDE simulation with Fourier Neural Operator surrogate modeling for fast, high‑accuracy thermal prediction and design exploration.
• ⭐(New! 2025-04) Design Optimization for Reaching Target Temperature [Doc] — Design optimization workflow coupling PDE‑based thermal simulation with optimization techniques to tune geometry and boundary conditions for achieving target temperature distributions.
• Battery pack Simulink model with Q-Bat and Simscape [Code/Model] — Combines Simscape and Q-Bat to simulate electrothermal behavior of a 14-cell battery pack with cooling plates and reduced-order thermal modeling for fault analysis and temperature-dependent performance.
• Import a Motor-CAD Thermal Model into Simulink and Simscape [Code/Model] — Imports Motor-CAD models into Simulink and generates reduced-order thermal models for motors, enabling integration into Simscape system-level simulations and faster-than-real-time thermal analysis.
• Battery Electric Vehicle with Motor Cooling in Simscape [Code/Model] — Simulates a BEV with a liquid-cooled motor executing a passing maneuver, measuring speed, torque, and temperature to assess system performance and cooling effectiveness.
• Vehicle HVAC System [Doc] — Models moist air flow in a vehicle HVAC system using Simscape Moist Air library, including heat exchange with the environment and psychrometric chart visualization.
• Electric Vehicle Thermal Management [Doc] — Simulates a BEV thermal system with coolant loops, refrigerant circuits, and cabin HVAC, supporting seasonal scenarios and control logic for pumps, valves, and compressors.
• EV Battery Cooling System [Doc] — Demonstrates a battery cooling system with cold plates, radiators, and refrigerant loops, analyzing heat flow and coolant behavior under drive cycle and fast charge conditions.
• Reduced-Order Model for Thermal Behavior of Battery [Doc] — Uses finite element analysis and modal decomposition to create reduced-order thermal models of battery cells for fast simulation and integration into Simscape.
• Analyze Battery Spatial Temperature Variation During Fast Charge [Doc] — Evaluates temperature gradients across battery cells during fast charging using Simscape Battery and PDE Toolbox, to seek uniform degradation and thermal safety.
• Thermal Analysis for New and Aged Battery Packs [Doc] — Compares thermal performance of new and aged battery packs under constant discharge, accounting for increased resistance and degraded cooling paths over lifecycle.
• Reduced Order Modeling of Battery Electric Vehicle Thermal Management System [Code/Model] — Uses deep learning to create a low-order nonlinear state-space model of a BEV battery system, enabling fast simulation and control design with thermal coupling.
• Predict EV Battery Temperature Using Cascade-Correlation Model [Doc] — Applies a cascade-correlation neural network to predict battery temperature based on current, SOC, and cooling conditions, supporting real-time thermal monitoring and control.

Applications, Technical Articles, and Presentations

• Mahindra Electric Uses System-Level Simulation to Optimize Battery Thermal Management System for an Electric Vehicle [Industry Example] — Mahindra Electric developed and validated a system-level simulation model using Simulink and Simscape to optimize battery cooling and refrigeration circuits, enabling efficient component selection and compressor logic tuning.
• Rapid System-Level Analysis and Control Design for EV Thermal Management Systems [Video] — Demonstrates how Simulink and Simscape enable fast modeling and control design for EV thermal systems, including refrigerant loops, coolant circuits, and drive cycle-based optimization.
• Reduced Order Modeling for Battery Thermal Analysis [Presentation] — Shows how to use finite element analysis and modal decomposition to create reduced-order thermal models of battery cells for fast simulation and integration into system-level models.
• Optimizing a Battery Electric Vehicle Thermal Management System [Video] — Explains how to use holistic simulation models to optimize BEV thermal systems for range, comfort, and energy efficiency, including sensitivity analysis and surrogate-based optimization workflows.

Vehicle Dynamics

Highlights

• Longitudinal Vehicle Motion: Simscape Essentials for Automotive Student Teams [Video, Code/Model] — Introduces students to vehicle modeling for competitions like Formula Student using Simscape, including a simple model of a non-driven vehicle braking while descending a slope.
• Simscape Vehicle Templates [Code/Model, Content Collection] — Provides configurable vehicle models for simulating conventional, hybrid, electric, and fuel cell vehicles, with modular components for suspension, braking, and ADAS testing.
• Vehicle Dynamics Blockset – Examples [Code/Model, Content Collection] — Offers preassembled vehicle dynamics models for passenger cars, trucks, and motorcycles, including propulsion, steering, suspension, and tire models, with support for Unreal Engine-based 3D simulation.

Educational and Training

• Solid Mechanics – Beam Bending and Deflection [Course Module] — Teaches beam bending and deflection using Symbolic Math Toolbox and MATLAB Live Scripts, including support reactions, moment diagrams, and deflection plots.
• Courseware on Finite Element Methods [Course Module] — Covers standard and advanced FEM formulations for Timoshenko beams and Reissner-Mindlin plates, with interactive Live Scripts and MATLAB Grader assignments.
• Control 101 toolbox – Suspension [Course Module] — Offers interactive tools and examples for learning control system fundamentals, including suspension modeling, PID tuning, and state-space analysis.
• Mass-Spring-Damper Systems [Course Module] — Provides guided activities and Simulink models to explore dynamics of mass-spring-damper systems, including free and forced vibration analysis.
• Translational and Rotational Vibrations Virtual Lab [Course Module, Code/Model] — Includes virtual labs for analyzing SDOF and MDOF vibration systems, absorber design, and control theory using MATLAB and Simscape.
• ChalmersX: Model-Based Automotive Systems Engineering [Online Course] — Teaches how to model and simulate system dynamics in automotive engineering using physical laws and control design principles.
• Model Predictive Control (MPC) virtual lab [Course Module] — Offers interactive exercises for designing linear and adaptive MPC controllers for vehicle steering systems using MATLAB and Simulink.
• Virtual Hardware and Labs for Controls – Cruise Control [Course Module] — Provides virtual mechanisms and labs for studying cruise control systems, including system identification, controller design, and simulation.
• Control 101 toolbox – Acceleration [Course Module] — Includes modules for modeling and controlling acceleration systems, with examples in PID tuning, feedback design, and state estimation.
• Interactive Live Script Control Tutorials for MATLAB and Simulink – Cruise Control [Course Module] — Features interactive tutorials for modeling and designing cruise control systems using MATLAB Live Scripts and Simulink.
• Multibody Simulation Onramp [Online Course] — Introduces Simscape Multibody for modeling mechanical systems, including joints, constraints, and CAD import workflows.
• Importing CAD Assemblies into Simscape Multibody [Video] — Demonstrates how to import CAD assemblies into Simscape Multibody, enabling simulation of mechanical systems with realistic geometry and motion.

Examples and Demos

• ⭐(New! 2026-04) Longitudinal Vehicle Performance Design [Doc] — Interactive Simulink app for defining and validating longitudinal vehicle performance targets such as acceleration, gradeability, top speed, and road-load parameters to support early-stage vehicle design and trade studies.
• ⭐(New! 2026-04) Regenerative and Friction Braking Control [Doc] — Model of blended regenerative and friction braking control for electric vehicles, capturing energy recovery, brake torque allocation, battery state-of-charge effects, and vehicle longitudinal dynamics using Simscape and control logic.
• ⭐(New! 2026-04) Custom Gear Library [Doc] — User-defined spur, helical, bevel, and planetary gear modeling with parameterized geometry, efficiency, losses, and compliance for extending Simscape Driveline gear libraries in detailed drivetrain simulations
• ⭐(New! 2026-04) Tire Manager App [Doc] — Centralized tire data management and parameterization app for creating, importing, validating, and deploying tire models across Vehicle Dynamics Blockset simulations.
• ⭐(New! 2026-04) Reference Path Generator [Doc] — Reference path generation block for creating smooth, time‑parameterized trajectories to support vehicle path following, driver‑in‑the‑loop testing, and automated driving simulations.
• ⭐(New! 2026-04) Fit a Tire Model to Tire Measurement Data [Doc] — Workflow for fitting and validating physics‑based tire models against measured tire test data to improve accuracy in vehicle dynamics simulations.
• ⭐(New! 2026-04) Convert Tire Model for Use in Supported Simulink Block [Doc] — Workflow for converting custom or third‑party tire models into compatible formats for use with supported Vehicle Dynamics Blockset tire blocks in Simulink.
• ⭐(New! 2026-04) Import Tire Measurement Data for Analysis [Doc] — Tire Manager–based workflow for importing, visualizing, and analyzing measured tire test data to support parameter fitting and validation of vehicle dynamics tire models.
• ⭐(New! 2026-04) Estimate Vehicle Drag Coefficients by Coast-Down Testing [Doc] — Coast‑down test–based estimation of aerodynamic drag and rolling resistance coefficients using Simulink Design Optimization for accurate longitudinal vehicle modeling.
• Model an Anti-Lock Braking System [Doc] — Simulates a single-wheel ABS system using slip-based control logic, mu-slip curves, and bang-bang control to illustrate braking dynamics and optimal friction conditions.
• Full Vehicle on Four Post Testrig [Doc] — Models a passenger vehicle on a four-post testrig to replicate vertical wheel motion and analyze suspension response, roll, pitch, and wheel hop frequencies.
• Frequency Response to Steering Angle Input [Doc] — Generates swept-sine steering commands for dynamic steering response testing, useful for ride and handling analysis and chassis control development.
• Estimate Vehicle Drag Coefficients by Coast-Down Testing [Doc] — Uses coast-down velocity data and parameter estimation to determine aerodynamic, rolling, and fixed drag coefficients based on SAE J1263 standards.
• Generate Skidpad Test [Doc] — Simulates a skidpad test for Formula Student vehicles, including path tracking, lap time estimation, and visualization of vehicle dynamics in 3D.
• Double Lane Change Reference Application [Doc] — Simulates ISO 3888-1/2 double lane change maneuvers to evaluate yaw stability, lateral acceleration, and obstacle avoidance performance.
• Kinematics and Compliance Virtual Test Laboratory [Doc] — Generates suspension parameters using Simscape Multibody and Model-Based Calibration Toolbox, comparing mapped and physical suspension responses.
• Vehicle Steering Gain at Different Speeds [Doc] — Analyzes steering gain and lateral dynamics using a slowly increasing steering maneuver based on SAE J266, with speed-dependent response evaluation.
• Vehicle Scenarios with Unreal Engine [Doc] — Integrates Unreal Engine with Simulink for 3D simulation of vehicle scenarios, enabling virtual testing of perception, control, and planning algorithms.
• Import RoadRunner Scene into Unreal Engine Using Simulink [Doc] — Shows how to import RoadRunner scenes into Unreal Engine for simulation, including semantic segmentation, depth data, and sensor modeling.
• Vehicle Suspension System Templates [Doc] — Provides templates for double wishbone, MacPherson, and pushrod suspensions, allowing simulation of roll, bounce, and road profile response.
• Configuring Dynamic Cameras - Vehicle Slalom [Doc] — Demonstrates how to configure dynamic camera views for vehicle slalom maneuvers in Simscape Multibody, enhancing visualization and analysis.
• Suspension System Comparison [Doc] — Compares different suspension architectures under identical road profiles, analyzing vertical force, camber, and toe angle responses.

Applications, Technical Articles, and Presentations

• ⭐(New! 2026-04) Tire Modeling Using Extended Tire Features for Vehicle Dynamics Blockset [Video] — End‑to‑end workflow for advanced tire modeling using Extended Tire Features in Vehicle Dynamics Blockset, covering nonlinear tire data import, Magic Formula fitting, and integration into Simulink vehicle dynamics simulations for improved handling accuracy.
• Continental Develops Electronically Controlled Air Suspension for Heavy-Duty Trucks [Industry Example] — Continental used Model-Based Design with MATLAB and Simulink to develop an electronically controlled air suspension system for 40-ton trucks, reducing hardware development time by six months and automating 90% of the code generation.
• Formula Student Driver-in-the-Loop Simulator Using Simulink and Unreal Engine [Video] — DynamiΣ PRC built a custom driver-in-the-loop simulator using Simulink and Unreal Engine for Formula Student, integrating full vehicle models and telemetry for dynamic event testing and driver training.
• Formula Student Vehicle Modeling Using Simscape Multibody [Video] — Demonstrates how to use Simscape Multibody to model a Formula Student vehicle with 14 degrees of freedom, enabling lap-time simulation, suspension testing, and performance optimization.
• Modeling Vehicle Dynamics [Video] — Explores nonlinear grey-box modeling of vehicle dynamics using a bicycle model structure, estimating tire stiffness and simulating longitudinal, lateral, and yaw motion.
• Determining Chassis Stiffness with MATLAB [Video] — Introduces the direct stiffness method for analyzing steel tube frames in racecars, demonstrating how to compute displacements and member forces using MATLAB and optimize truss structures.
• Simulating Longitudinal and Lateral Vehicle Dynamics [Video] — Shows how to simulate vehicle dynamics using Vehicle Dynamics Blockset, including autonomous and racecar scenarios, and analyzing surface effects on motion.
• One-Pedal Driving Rapid Feature Development With Simulink – General Motors [Presentation] — GM engineers used Simulink to rapidly develop the One-Pedal Driving feature for the Chevrolet Bolt EV, enabling coast regeneration and intelligent speed control with 90% of the software written in Simulink.

Optimization and Efficiency

Highlights

• Electric Vehicle Modeling: Powertrain, Battery, and Thermal Systems [Video, Presentation] — Demonstrates how to build and optimize a full EV model using Virtual Vehicle Composer, including battery pack sizing, thermal management, and system-level validation.
• Analyze Power and Energy – Virtual Vehicle Composer [Doc] — Provides a live script for analyzing power and energy flow in EV models, generating efficiency reports, Sankey diagrams, and subsystem-level summaries using Power Accounting Bus Creator blocks.
• Improve Motor Efficiency with Optimized Control Parameters [Doc] — Uses field-oriented control and optimization techniques to minimize motor losses in a PMSM drive, including tuning d-axis and q-axis currents based on torque and speed demands.

Educational and Training

• ⭐(New! 2026-04) Run Multiple Simulations in Parallel [Online Course] — Self-paced course that shows how to speed up analysis and design workflows by running parameter sweeps, Monte Carlo studies, and other simulation workloads in parallel using MATLAB and Simulink.
• Common Data Analysis Techniques [Online Course] — Teaches how to explore relationships between variables, perform polynomial fitting, and apply linear correlation techniques to extract insights from datasets.
• Optimization Onramp [Online Course] — Introduces the basics of solving constrained and unconstrained optimization problems in MATLAB, including defining variables, objective functions, and constraints.
• Machine Learning Techniques in MATLAB [Online Course] — Covers classification and regression methods, model training, and deployment using MATLAB and Simulink, with hands-on exercises and automated feedback.
• Battery Systems: introduction [Course Module] — Offers foundational training in battery pack design, cell modeling, and battery management systems using MATLAB, Simulink, and Simscape.
• Design Optimization with MATLAB [Video] — Demonstrates how to use Optimization Toolbox and Global Optimization Toolbox to define and solve design optimization problems across engineering domains.
• Mathematical Modeling with Optimization [Video Series] — Explains how to transform real-world problems into mathematical programs and solve them using linear, nonlinear, and mixed-integer optimization techniques.
• Solving Optimization Problems with MATLAB – Master Class with Loren Shure [Video] — A comprehensive master class covering solver-based and problem-based approaches, optimization workflows, and solver selection for various problem types.
• Linear Programming [Content Collection] — Provides resources for solving linear optimization problems using interior-point and simplex algorithms, with applications in manufacturing, finance, and energy.
• Nonlinear Programming [Content Collection] — Covers solving nonlinear optimization problems with constraints using algorithms like SQP, trust-region, and interior-point methods.
• Genetic Algorithm [Content Collection] — Explains how to use genetic algorithms for global optimization, including mutation, crossover, and elitism strategies for solving complex problems.
• Surrogate Optimization [Content Collection] — Describes how to use surrogate models to approximate expensive simulations and optimize design parameters efficiently.
• Surrogate Optimization [Video] — Demonstrates how surrogate optimization can solve complex design problems with minimal evaluations using simulation-based models.
• Integer Programming [Content Collection] — Offers tools for solving mixed-integer linear and nonlinear problems, useful for scheduling, resource allocation, and discrete optimization.
• How to Use the Problem-Based Optimize Live Editor Task [Video] — Shows how to interactively define and solve optimization problems using the Live Editor, including constraints, objectives, and solver selection.

Examples and Demos

• ⭐(New! 2026-04) Calculate Five-Cycle Electric Vehicle Range Adjustment Factor [Doc] — Calculate the EPA 5‑cycle electric vehicle range adjustment factor in Vehicle Dynamics Blockset to convert simulated drive‑cycle energy consumption into a regulatory‑aligned real‑world EV range estimate.
• ⭐(New! 2026-04) Simulate Five-Cycle Energy Consumption Tests Using Virtual Vehicle Model [Doc] — Use the Virtual Vehicle Composer to simulate EPA five‑cycle energy consumption tests and evaluate electric vehicle efficiency and range using standardized regulatory drive cycles.
• ⭐(New! 2026-04) Improve an Engine Cooling Fan Using Design for Six Sigma Techniques [Doc] — Design for Six Sigma–based engine cooling fan improvement using statistical modeling, DOE, and robustness analysis to reduce variability and enhance thermal performance.
• ⭐(New! 2026-04) Optimization Explorer App [Doc] — Explore multiple solver configurations and their solutions for an optimization problem
• Electric Vehicle Design with Simscape [Code/Model] — Provides a comprehensive BEV model built with Simscape libraries for range estimation, battery sizing, gear ratio selection, motor loss mapping, and thermal analysis, including neural network-based virtual sensors and inverter lifetime prediction.
• Design and Analyze a Battery Electric Vehicle with Thermal Management [Video] — Demonstrates how to build a virtual BEV model with powertrain, driveline, and thermal subsystems to assess range and consumption under different ambient conditions and drive cycles.
• Design and Analyze a Battery Electric Vehicle with Thermal Management [Code/Model] — Offers a GitHub repository with a Simscape-based BEV model including electric powertrain, coolant and refrigerant loops, and cabin HVAC, designed for thermal optimization and control algorithm development.
• Calibrate ECMS Block for Objective Hybrid Vehicle Fuel Economy Assessment [Doc] — Provides a script to calibrate the ECMS weighting factor for hybrid vehicles, ensuring net-zero battery SOC change over a drive cycle and accurate fuel economy estimation.
• Optimize Transmission Control Module Shift Schedules [Doc] — Uses the conventional vehicle reference application to optimize TCM shift maps for improved fuel economy and performance, leveraging global optimization and parallel computing.
• Least Squares [Doc] — Offers tools for solving linear and nonlinear least-squares problems, including curve fitting, ODE parameter estimation, and problem-based optimization workflows.
• Systems of Nonlinear Equations [Doc] — Explains how to solve multivariable nonlinear equations using MATLAB's fsolve and problem-based approaches, with support for Jacobian computation and solver customization.

Applications, Technical Articles, and Presentations

• ⭐(New! 2025-10) Accelerating Vehicle Controls Development with Cloud-Based MIL Simulation [Video] — McLaren uses cloud‑based model‑in‑the‑loop simulation with MATLAB and Simulink to accelerate vehicle controls development through early virtual validation, scalable workflows, and reduced reliance on physical prototypes.
• ⭐(New! 2025-10) Optimize Vehicle Design with AI and Simscape [Video] — AI‑driven surrogate models combined with Simscape physical modeling enable rapid design‑space exploration and multi‑objective optimization of vehicle systems, accelerating early‑stage vehicle design decisions.
• ⭐(New! 2025-11) How to Optimize DC Fast Charging to Balance Speed and Battery Life [Video] — High‑fidelity battery modeling and model predictive control in MATLAB and Simulink can optimize DC fast‑charging strategies to minimize charging time while protecting battery health by avoiding lithium plating and excessive degradation.
• ⭐(New! 2025-11) Model-Based Optimization of Drive Cycle Efficiency in Electric Two-Wheelers [Video] — Model‑based workflow using MATLAB and Simulink to optimize drive‑cycle efficiency in electric two‑wheelers by combining system‑level simulation, high‑fidelity motor models, and control optimization to improve real‑world energy efficiency and range.
• Smart, Green Technology Is Changing the Way India Rides [Industry Example] — Ather Energy developed smart electric scooters with connected features and efficient lithium-ion batteries, transforming urban mobility in India and reducing greenhouse gas emissions from two-wheelers.
• Tesla's secret to winning "The Range Game" [Industry Example] — Tesla improved EV range by optimizing motor efficiency, powertrain components, and energy flow using MATLAB models, achieving up to 402 miles of range without increasing battery capacity.
• Optimising the Energy Efficiency of Electric Vehicles with Simulink and Simscape [Video] — Polestar developed a modular simulation platform using Simulink and Simscape to optimize energy management across propulsion, thermal, and control systems for next-generation EVs.
• System Modelling & Simulation of an Electric Two-Wheeler: A Journey from Virtual Prototyping to Production [Video] — Demonstrates how to design and test electric two-wheelers using virtual simulation for powertrain sizing, ABS and regenerative braking algorithms, and embedded software validation.
• Top 7 Use Cases for Electric Vehicle Simulation [Technical Article] — Highlights key EV simulation tasks including powertrain architecture exploration, regenerative braking tuning, suspension design, ADAS validation, and hardware-in-the-loop testing.
• EV Charging Infrastructure: Enabling Sustainable Mobility [Video] — Discusses strategies for deploying EV charging stations, aligning demand with grid capacity, and optimizing asset planning using MATLAB and Simulink for sustainable transportation.

Advanced Driver Assistance and Automated Driving Systems (ADAS/ADS)

Highlights

• ADAS Learning Resources for Students [Content Collection] — Offers a curated set of tutorials, documentation, and videos for students working on ADAS and automated driving projects, covering topics like sensor fusion, path planning, perception, and scenario generation using MATLAB, Simulink, and RoadRunner.

Educational and Training

• Vehicle path tracking using Stanley Controller [Video, Code/Model] — A tutorial on implementing a Stanley controller for autonomous vehicle path tracking using MATLAB and Simulink, covering waypoint generation, reference input calculation, model building, and trajectory visualization.
• Autonomous navigation series [Video] — A video series introducing key concepts in autonomous navigation including localization, SLAM, path planning, extended object tracking, and system performance metrics.
• Getting started with RoadRunner [Video] — Demonstrates how to use RoadRunner to design 3D roadway scenes, configure traffic signals, and export environments for automated driving simulation.
• Autonomous Navigation for Highway Driving: Design and Simulate Lane Change Maneuver System [Video] — Shows how to design and test an automated lane change maneuver system using Automated Driving Toolbox and Navigation Toolbox, including vehicle dynamics, sensors, and control logic.
• Introduction to Automated Driving Toolbox [Video] — Explains how to use Automated Driving Toolbox to visualize sensor data, detect and track objects, and simulate ADAS and autonomous driving systems.

Examples and Demos

• ⭐(New! 2026-04) Cosimulate Simulink and Eclipse SUMO Traffic Simulator [Doc] — Simulink–Eclipse SUMO co-simulation workflow for automated driving, enabling bidirectional traffic data exchange, dynamic actor spawning, and large-scale urban traffic scenarios for ADAS and autonomous vehicle testing
• ⭐(New! 2026-04) SUMO Traffic Simulation with RoadRunner Scenario [Doc] — RoadRunner–Eclipse SUMO integrated traffic simulation workflow for generating realistic urban traffic, synchronizing RoadRunner scenarios with microscopic traffic flow, and supporting automated driving and ADAS validation in large‑scale road networks
• ⭐(New! 2026-04) Get Started with Euro NCAP Test Suite [Doc] — Test Suite for Euro NCAP® workflow for generating and simulating large sets of driving scenario variants by systematically varying scene, actor, and event parameters to support exhaustive safety assessment and standards-based testing of ADAS and autonomous driving systems.
• ⭐(New! 2026-04) Automatically Label Ground Truth Using Vision-Language Model [Doc] — Automatic image labeling workflow using vision‑language models in MATLAB for accelerating dataset annotation with natural‑language prompts, pretrained multimodal AI, and computer vision training pipelines
• ⭐(New! 2026-04) Automate Ground Truth Labeling for Instance Segmentation [Doc] — Automated instance‑segmentation ground truth generation using pretrained SOLOv2 models to create polygon labels within the Video Labeler app, accelerating dataset annotation and model training workflows
• ⭐(New! 2026-04) Collision Authoring Tool [Doc] — Collision scenario authoring in RoadRunner Scenario for defining precise vehicle‑to‑vehicle impact points, timing‑critical interactions, and safety validation workflows in automated driving simulations
• ⭐(New! 2026-04) Import Scenarios from ASAM OpenSCENARIO XML Files [Doc] — ASAM OpenSCENARIO XML import workflow for RoadRunner Scenario, enabling reuse of industry‑standard driving scenarios, editable actor logic and trajectories, and seamless integration into automated driving simulation pipelines
• Simulate RoadRunner scenarios with MATLAB and Simulink [Doc] — Explains how to co-simulate RoadRunner scenarios with MATLAB and Simulink, including actor modeling, sensor integration, simulation control, and result analysis using ASAM OSI format.
• Add sensors to RoadRunner scenario [Doc] — Shows how to define sensor models in MATLAB and add them to vehicle actors in RoadRunner scenarios, enabling ground truth extraction and detection visualization.
• Autonomous Emergency Braking with vehicle dynamics and Unreal Engine [Doc] — Demonstrates how to simulate an AEB system using a 14-DOF vehicle dynamics model, vision and radar sensors, and Unreal Engine for 3D visualization and terrain interaction.
• Test Closed-Loop ADAS Algorithm Using Driving Scenario [Doc] — Uses a prebuilt Euro NCAP scenario to test an AEB algorithm in Simulink, integrating sensor fusion, scenario reading, and controller logic in a closed-loop simulation.
• Automate Ground Truth Labeling Across Multiple Signals [Doc] — Describes how to use the Ground Truth Labeler app and automation algorithms to label camera and lidar data simultaneously, improving efficiency and accuracy in training datasets.
• Simulate Radar Ghosts Due to Multipath Return [Doc] — Simulates ghost detections caused by multipath reflections in radar systems, using statistical and transceiver models to analyze detection artifacts and improve tracking algorithms.
• Visualize Automated Parking Valet Using Unreal Engine Simulation [Doc] — Shows how to visualize vehicle motion in a 3D Unreal Engine environment for an automated parking valet system, including costmap generation, route planning, and scene configuration.

Technical Articles and Presentations

• ⭐(New! 2025-09) Cone Detection Using Deep Learning for Formula Student Driverless [Video] — Formula Student Driverless teams use deep learning workflows in MATLAB to train, validate, and deploy cone detection algorithms for reliable real‑time perception in autonomous race vehicles.
• ⭐(New! 2025-11) Virtual Simulation Environment for Traffic Sign Recognition Systems [Video] — Use a virtual simulation environment with MATLAB and Simulink to design, test, and validate traffic sign recognition systems for ADAS and automated driving under diverse, repeatable scenarios.
• An ISO 26262 Workflow for Automated Driving Applications Using MATLAB: Guidelines and Best Practices [Technical Article] — Provides best practices for using MATLAB and Simulink to meet ISO 26262 safety standards in ADAS development, including requirement linking, static model analysis, MIL/SIL/PIL testing, and documentation strategies.
• Visualize, Label, and Fuse Sensor Data for Automated Driving [Technical Article] — Explains how to use Automated Driving Toolbox to visualize sensor data, automate ground truth labeling, fuse radar and vision detections, and synthesize sensor data for scenario testing.
• Implementing a Hybrid Vehicle-in-the-Loop Testing Methodology for Automated Driving Functions [Technical Article] — Details a hybrid testing approach combining real vehicle dynamics with virtual environments to safely validate ADAS features like lane keeping and emergency braking.
• Harvesting Driving Scenarios from Recorded Sensor Data at Aptiv [Technical Article] — Outlines a workflow using MATLAB and RoadRunner to convert recorded sensor data into virtual driving scenarios for simulation-based testing of ADAS algorithms.
• A Conceptual Framework for ADAS/AD Safety [Presentation] — Introduces a framework based on ISO 21448 (SOTIF) for validating ADAS safety, emphasizing scenario coverage, sensor limitations, and foreseeable misuse.
• Scaling Virtual Validation for ADAS Features [Video] — Discusses how to scale ADAS validation using Euro NCAP scenarios, recorded sensor data, and automated test frameworks across compute infrastructures.
• AD/ADAS Country-Based Virtual Validation Using Real-World Data [Video] — Explores how to enhance simulation models with country-specific features and real-world data using MATLAB, Simulink, and RoadRunner for global ADAS validation.
• Master Class: Scenario-Based Virtual Validation for ADAS Features [Presentation] — Demonstrates how to use RoadRunner and RoadRunner Scenario to create, parameterize, and automate ADAS test scenarios for highway lane changes and other maneuvers.
• A Cross-Domain Simulation Platform for ADAS and AD [Presentation] — Bosch Engineering presents a simulation platform integrating radar-based ADAS features, ECU calibration, and automated scenario execution for virtual testing.

Applications

• Toyota Aims to Realize "Seasoned Driving" for Automated Driving System [Industry Example] — Toyota developed a model predictive control (MPC) algorithm to replicate the nuanced behavior of skilled human drivers, using MATLAB and Simulink to simulate and optimize driving trajectories.
• Developing Low-Speed Motion Control Algorithms for Automated Driving Functions at ZF [Industry Example] — ZF used Model-Based Design with MATLAB and Simulink to create a scalable platform for developing motion control algorithms for low-speed autonomous maneuvers, reducing in-vehicle tuning and enabling future autonomy features.
• Automated Driving Simulations with a 3D Digital Twin [Industry Example] — Waseda University students used Simulink and RoadRunner to simulate hybrid vehicle performance in a classroom setting, enhancing understanding of fuel economy and emissions through digital twin modeling.
• Seeing the Road Ahead – The Path Toward Fully Autonomous, Self-Driving Cars [Industry Example] — Highlights advances in radar, lidar, and AI technologies for vehicle perception, showing how autonomous systems can outperform human drivers in detecting and reacting to road conditions.
• Mazda Builds Design Concept MILS Environment for Autonomous Driving [Industry Example] — Mazda created a MILS simulation environment using Simulink and Automated Driving Toolbox to test merging decision algorithms, integrating deep learning and traffic simulation for early-stage validation.
• Simulating Autonomous Driving Algorithms for the SAE AutoDrive Challenge [Industry Example] — Texas A&M used Simulink and Unreal Engine to simulate and test autonomous vehicle algorithms for the SAE AutoDrive Challenge, enabling parallel development and reducing reliance on physical testing.
• Bosch Demonstrates Cosimulation for Virtual Automated Driving [Industry Example] — Bosch developed a cosimulation framework using MATLAB, Simulink, RoadRunner, and CarMaker to model complex traffic scenarios and validate autonomous driving systems with hardware- and software-in-the-loop testing.

Model-Based Systems Engineering (MBSE)

Highlights

• Model-Based Systems Engineering [Content Collection] — Provides a unified environment using MATLAB, Simulink, System Composer, and Requirements Toolbox to define system architectures, link requirements, perform trade studies, and validate designs through simulation, enabling a digital thread across the development lifecycle.
• ⭐(New! 2026-04) Interface to access projects in SysML v2 repository [Doc] — Access SysML® v2-compliant remote repositories in System Composer programmatically.

Educational and Training

• System Composer Onramp [Online Course] — Introduces System Composer for model-based systems engineering, including architecture modeling and integration with Simulink.
• Model Based Life-Cycle with MATLAB and Simulink [Course Module] — Covers the full model-based development lifecycle using MATLAB and Simulink for engineering applications.
• Intro to Systems Engineering [Video] — A video series introducing systems engineering concepts and tools using MATLAB and Simulink.
• Why Models Are Essential to Digital Engineering [Video] — Explores the role of modeling in digital engineering for improving design accuracy and collaboration.
• Engineering Problem Solving [Course Module] — Teaches structured approaches to solving engineering problems using MATLAB and Simulink.

Examples and Demos

• EV power flow with system composer [Code/Model] — GitHub repository demonstrating EV power flow modeling using System Composer.
• Integrate Components from External Tools [Doc] — Documentation on co-simulation and multithreaded integration of external components in Simulink.
• Parameter Tuning for Digital Twins [Doc] — Guide to deploying parameter estimation workflows for digital twin applications using Simulink Compiler.
• Battery Sizing and Automotive Electrical System Analysis [Doc] — Describes how to use metadata in System Composer for battery sizing and electrical system analysis in automotive applications.

Applications, Technical Articles, and Presentations

• ⭐(New! 2025-11) Drive Automotive Software Excellence: A High-Quality, End-to-End MBD Environment [Video] — End‑to‑end Model‑Based Design environment enables standardized, traceable, and continuously delivered automotive control software by integrating requirements, development, testing, and validation into a high‑quality digital workflow.
• Rivian Scales Full-Vehicle Simulations with MATLAB and MATLAB Parallel Server [Industry Example] — Rivian developed a scalable simulation platform using MATLAB and Simulink to democratize full-vehicle simulations across engineering teams.
• Building a Hybrid Electric Vehicle Prototype System for Processor-in-the-Loop Simulations [Industry Example] — NXP engineers used Simulink and Powertrain Blockset to build a processor-in-the-loop simulation system for hybrid vehicle control algorithms.
• Feature-Driven eDrive Development: A Consistent Way to Handle Complexity [Video] — Explains how combining MBSE and Model-Based Design improves eDrive system development and traceability across engineering domains.
• Enhancing BMS Software Development with Model-Based Design and IEC Certification Kit [Video] — Shows how FEV uses Model-Based Design and IEC Certification Kit to streamline battery management system development and enable streamlined compliance.
• Multi-domain Model-driven Development, Developing Electrical Propulsion System at Volvo Cars [Presentation] — Volvo Cars adopted model-driven development and continuous integration to manage the complexity of electric propulsion systems.
• One-Pedal Driving Rapid Feature Development With Simulink - General Motors [Presentation] — GM used Simulink to rapidly develop and deploy One-Pedal Driving for the Chevrolet Bolt EV, enhancing regenerative braking and driving experience.