BAttery Management Systems

Develop battery management systems with Simulink

Lithium-ion battery packs are the predominant energy storage systems in aircraft, electric vehicles, portable devices, and other equipment requiring a reliable, high-energy-density, low-weight power source. The battery management system (BMS) is responsible for safe operation, performance, and battery life under diverse charge-discharge and environmental conditions. When designing a BMS, engineers develop feedback and supervisory control that:

  • Monitors cell voltage and temperature
  • Estimates state-of-charge and state-of-health
  • Limits power input and output for thermal and overcharge protection
  • Controls the charging profile
  • Balances the state-of-charge of individual cells
  • Isolates the battery pack from the load when necessary

Simulink® modeling and simulation capabilities enable BMS development, including single-cell-equivalent circuit formulation and parameterization, electronic circuit design, control logic, automatic code generation, and verification and validation. With Simulink, engineers can design and simulate the battery management systems by:

  • Modeling battery packs using electrical networks whose topology mirrors that of the actual system and scales with the number of cells
  • Parameterizing equivalent circuit elements using test data for accurate representation of cell chemistry
  • Designing the power electronics circuit that connects the pack with the controls
  • Developing closed-loop control algorithms for supervisory and fault detection logic
  • Designing state observers for state-of-charge and state-of-health online estimation

Using Simulink, engineers can exercise the battery management system over a range of operating and fault conditions before committing to hardware testing. You can generate C code from Simulink models to deploy your control algorithms for rapid prototyping of systems or microcontrollers. Simulink generates code from the battery and electronic component models, letting you perform real-time simulation for hardware-in-the-loop (HIL) testing to validate your BMS before hardware implementation.

How to Develop Battery Management Systems in Simulink (video series)

This video series walks through how to model and simulate algorithms for a battery management system (BMS) using Simulink® and Stateflow®. You’ll see how a BMS simulation model lets you explore a wider range of operational and environmental conditions that would be difficult to reproduce with hardware testing. You’ll learn:

  • How to use Simulink to model and test components and subsystems
  • How to use Stateflow to develop supervisory control for a battery management system
  • How state-of-charge (SoC) algorithms are modeled in Simulink
  • How to model cell balancing algorithms in Simulink

Part I: Battery Management Systems (BMS) Overview

Learn how to use Simulink to model and test components and subsystems of a battery management system (BMS). Watch video here (5:28)

Part II: The BMS Algorithm

Learn how to use Stateflow to develop supervisory control for a battery management system. Watch video here (3:11)

Part III: State of Charge Estimation

Learn how to model state-of-charge (SoC) algorithms in Simulink. Watch video here (2:46)

Part IV: Cell Balancing

Learn how to model cell balancing algorithms in Simulink. Watch video here (4:32)

White Paper: Developing Battery Systems with Simulink and Simscape

Electrification is driving the use of batteries for a range of applications, including electric vehicles, ships, electric aircraft, grid-tied energy storage systems, and photovoltaic systems. These applications have different requirements for battery system design.

Discover how Simulink® and Simscape Battery™ support the design and development of battery systems, including:

  • Battery pack design
  • Battery thermal management design
  • Battery management system (BMS) algorithm development
  • Component integration and system simulation
  • Hardware-in-the-loop testing and deployment
Read White Paper here

How to Estimate Battery State-of-Charge (SOC) Using Deep Learning

To say that lithium-ion batteries are important in our lives would be an understatement. They are everywhere—from our mobile phones, laptops, and wearable electronics to electric vehicles and smart grids—so knowing how long their charge will last is important, too!

The focus of this video series is the application of neural networks to battery state of charge estimation. State of charge estimation is the task of the battery management system, or BMS. An accurate determination of the State of Charge (SOC) in a battery indicates to the user how long they can continue to use the battery-powered device before a recharge is needed. In a car, for example, an accurate knowledge of the time to recharge reduces anxiety and allows for appropriate trip planning.

This video series has four parts:

  • An Introduction to Battery State of Charge Estimation
  • The Experiment Using Neural Networks
  • Neural Networks for SOC Estimation
  • Training and Prediction in MATLAB and Simulink Implementation

The materials presented in this video series are the result of the work done by Carlos Vidal and Phil Kollmeyer, both researchers at McMaster University in Hamilton, Ontario. The work was done in collaboration with engineers from FCA and published last year as an SAE paper.

Part I: An introduction to Battery State-of-Charge Estimation

Get an introduction of battery state of charge (SOC) estimation, including a review of using neural networks. Watch video here (5:17)

Part II: The Experimenmt Using Neural Networks

Discover the experimental process involved in training and testing the neural network. Watch video here (8:55)

Part III: Neural Networks for SOC Estimation

Explore the theory and implementation of the deep neural network used in this study; motivation and tradeoffs for the utilization of certain network architectures; and training, testing, validation, and analysis of the network performance. Watch video here (8:16)

Part IV: Training and Prediction in MATLAB and Simulink Implementation

See the neural network training process and the Simulink implementation of the method. See video here (7:41)

Verifying, Validating and Testing Battery Management Systems

A battery management system (BMS) maintains the health and safe operation of batteries in a variety of systems such as electric vehicles, aircraft, medical devices, and portable electronics. Using Simulink® to develop and test BMS software helps engineers meet industry standards like ISO 26262 and IEC 62304.

In this video series, you’ll see the methods and techniques you can adopt in Simulink to verify, validate, and test a BMS model against requirements before deploying the software onto an embedded microprocessor. The series demonstrates how to:

  • Author, analyze, and manage requirements
  • Link and trace requirements to source documents
  • Conduct model and software coverage analysis
  • Manage multiple tests, view results, and generate reports
  • Use generated code for software-in-the-loop (SIL) and processor-in-the-loop (PIL) testing
  • Perform closed-loop testing to verify BMS logic
  • Perform hardware-in-the-loop (HIL) testing to validate BMS embedded software

Part I: Introduction to Testing Battery Management System (BMS) Software

Learn the fundamental aspects of verification, validation, and testing activities for a battery management system (BMS). Watch video here (7:07)

Part II: Managing Requirements for Batter Management Systemns (BMS) in Simulink

See how to use Simulink Requirements to author, analyze, and manage battery management system (BMS) requirements in Simulink. Link and trace requirements between a Simulink model and source documents. Watch video here (15:37)

Part III: Unit Testing for Battery Management System (BMS) Software in Simulink

Discover how to use Simulink Test to verify a battery management system (BMS) software component in Simulink. Watch video here (5:59)

Part IV: Managing Battery Management System (BMS) Tests in Simulink

Discover how to use the Simulink Test Manager to manage multiple tests, view results, and generate reports for your battery management system (BMS). Watch video here (15:23)

Part V: Measuring and Improving Battery Management System (Test Coverage)

Learn how to measure and improve test input coverage for your battery management system (BMS) model. Watch video here (8:49)

Part VI: Generating Code for a BVattery Management System (BMS)

Learn how to generate C code from your battery management system (BMS) model. Watch video here (5:09)

Part VII: Testing Generated Code for a Battery Management System (BMS)

See how to conduct software-in-the-loop (SIL) and processor-in-the-loop (PIL) testing for code generated from a battery management system (BMS). Watch video here (7:32)

Part VIII: Closed-Loop Testing of a Battery Management System (BMS)

See how to perform closed-loop testing to verify battery management system (BMS) logic. Watch video here (5:13)

Part IX: Hardware-in-the-loop Simulation for Battery Management System (BMS)

This video demonstrates how to use Simulink, Simscape, Simulink Real-Time, and Speedgoat real-time systems to perform hardware-in-the-loop (HIL) simulation to validate and test a battery management system. Watch video here (12:39)

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