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Electrical

Modified on

08 May 2023 10:04 pm

Modeling of Electric Vehicles using MATLAB Simulink

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Skill-Lync

Electric vehicles have been gaining popularity worldwide due to their environmentally friendly and cost-effective nature. However, designing exemplary architecture and selecting appropriate components for the modeling of electric vehicles can be daunting, given the plethora of options available in today's market. As an electromechanical system with multiple subsystems, the seamless integration of all these subsystems is crucial for achieving maximum efficiency and performance. Unfortunately, testing all possible combinations of subsystems is not practical or feasible, making simulation tools essential for evaluating critical parameters such as acceleration, range, system cost, and power.

Electric Vehicles using MATLAB Simulink

One of the most powerful and versatile simulation tools available for the modeling of electric vehicles is MATLAB Simulink. This software provides a graphical user interface for modeling, simulating, and analyzing dynamic systems, making it an ideal choice for electric vehicle design. With Simulink, designers can create models of multiple subsystems that can be optimized and designed independently, reducing design time and improving system performance.

In this blog, we will explore everything you need to know about the mathematical modeling and simulation of electric vehicles using MATLAB and Simulink to help you design efficient, high-performing electric vehicles. Continue reading to learn more.

Why Choose MATLAB and Simulink for Modeling Electric Vehicles?

The development of electric vehicles (EVs) can be complex and challenging. However, MATLAB® and Simulink® can help engineers streamline this process using data and models. By leveraging pre-built reference applications, the barrier for simulation can be lowered, enabling engineers to front-load their development efforts.

With MATLAB and Simulink models of electric vehicles, engineers can:

  • Leverage Model-Based System Engineering to create complicated EV designs and optimize systems.
  • Create battery models and BMS (Battery Management Systems).
  • Model FCS (Fuel Cell Systems) and develop FCCS (Fuel Cell Control Systems).
  • Create traction motor models and MCU (Motor Control Units).
  • Deploy, fuse, and test control algorithms.
  • Utilize data-driven processes and AI (Artificial Intelligence) in Electric Vehicle development.

 

Benefits of Leveraging MATLAB and Simulink for Electric Vehicle Modeling

Leveraging MATLAB and Simulink for Electric Vehicle modeling offers numerous benefits, including:

  • Design and Simulate System Architecture for Electric Vehicles

Electric vehicles require multi-domain system integration design and analysis at the vehicle level. With MATLAB and Simulink, you can benefit from the following:

  • Using pre-built reference applications for basic powertrain configurations, you can quickly have a complete EV simulation with generators, motors, and energy storage components operating.
  • Analyze motor and battery size, architecture tradeoffs, and control parameter optimization, among other things.
  • In a single environment, integrate, analyze, and test multi-domain systems.
  • Using digital traces across models from multiple process phases, detailed design, capture system architecture, and implementation details in a single environment.
  • For increased efficiency and productivity, reuse models throughout the design cycle, from architecture and analysis through HIL (hardware-in-the-loop) testing.
  • Model Batteries and Develop Building Management Systems (BMS)

Accurate battery modeling is essential for developing batteries and BMS for electric vehicles' diverse charge-discharge and environmental conditions. With MATLAB and Simulink, you can take advantage of the following capabilities:

  • Model and simulate batteries, enabling the development of BMS.
  • Use equivalent circuits to model batteries and enhance fidelity together with elaborate circuit topologies.
  • Simulate thermal effects, non-linearities, battery degradation, and SOC/SOH.
  • Develop BMS, including automatic code generation, control logic, and closed-loop simulation for certification workflows and AUTOSAR.
  • Incorporate essential BMS functionalities, such as thermal and overcharge protection, voltage and temperature monitoring, and cell balancing and isolation.

These capabilities enable accurate battery modeling and BMS development, leading to improved performance and longevity of EV batteries.

Modelling of EV with Simulink & MATLAB

  • Designing Fuel Cell Systems and Developing Control Systems for Optimal Performance

Accurate FCS (fuel cell systems) modeling, like PEM (Polymer electrolyte membrane), frontloads development of FCS and FCCS (fuel cell control systems) across many operating and environmental conditions. With MATLAB and Simulink, you can: 

  • FCS modeling and simulation, as well as FCCS development
  • PEM fuel cells may be modeled using first principles based on electrochemistry or experimental data.
  • Fuel efficiency, performance, and heat impacts in fuel cell electric vehicles simulation.
  • With support for AUTOSAR and certification procedures, you may enable FCCS development, including automated code creation, control logic, and closed-loop validation.
  • Accomplish voltage, current, thermal management, and power monitoring functionalities.
  • Transforming Electric Vehicle Development with Data-Driven Workflows and Artificial Intelligence

By leveraging real-world driving and test data, you can inform design decisions, create reduced-order models to accelerate simulations, and develop maintenance services. MATLAB and Simulink offer powerful tools to facilitate these tasks:

  • Employ the complete AI workflow, from data preparation to deployment on various platforms, including embedded hardware, edge devices, cloud, or enterprise servers.
  • Start with pre-built algorithms, models, reference examples for AI modeling, and access to a range of data sources such as databases, cloud sources, and binary files like MDF.
  • Train models using intuitive, point-and-click apps for both machine learning and deep learning.
  • Leverage AI models from the broader community through transfer learning and seamless deployment.
  • Integrate AI into system-wide models, simulate and verify before transitioning to hardware, and use AI capabilities to predict remaining useful life, enable predictive maintenance, build digital twins, and implement AI in Simulink.
  • Designing Traction Motors, Model Inverters, and Motor Control Software

By accurately modeling motors, it's possible to frontload the motor and motor control units (MCU) design prior to hardware testing. With the help of MATLAB and Simulink, you can:

  • Model and simulate power electronics, motors, and MCUs at the desired level of fidelity, ranging from system level to control and motor design levels. Features such as automated parameter estimation make it easier to achieve accurate modeling.
  • Design, simulate, and verify power conversion systems leveraging pre-built model libraries of power semiconductors, energy sources, and machines such as PMSM (permanent magnet synchronous motors) and IM (induction motors).
  • Develop MCUs using intuitive blocks for automated tuning of PID controllers, developing and tuning field-oriented control, closed-loop simulations, and automatic code generation. These simulations include HIL (Hardware-in-the-Loop) testing and support for certification workflows and AUTOSAR.
  • Implementing, Integrating, and Testing Control Algorithms

As safety standards become increasingly crucial for EV developers, MATLAB and Simulink offer robust tools to comply with regulations and ensure functional safety. You can:

  • Generate optimized C and HDL code automatically.
  • Measure model/code quality, trace requirements, and automatically generate test cases.
  • Use an ISO 26262 reference workflow to adhere to functional safety requirements.
  • Leverage pre-qualified tools for ISO 26262 compliance.
  • Model AUTOSAR software components with the AUTOSAR Blockset (adaptive and classic), import/export ARXML files, and simulate compositions. 
  • Generate code, integrate with CI/CD/CT pipelines, automate regression testing, and package for deployment.

Conclusion

Rapidly evolving electric vehicle technology demands careful assessment of its impact on design. A configurable simulation model can effectively explore various tradeoffs throughout the development process without risk. MATLAB and Simulink offer powerful tools to facilitate this process. And having proficiency in modeling electric vehicles with MATLAB and Simulink can be highly beneficial in this regard.

Skill-Lync can help you develop the expertise to effectively model electric vehicles using MATLAB and Simulink, giving you a valuable skill set in this rapidly evolving field. Talk to our experts and start your learning journey.


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Anup KumarH S


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