MATLAB and Simulink Training

Course Details

This two-day course focuses on modeling battery packs using Simscape™ and designing key control functionalities of battery management system using Stateflow®.

Topics include:

  • Perform cell characterization
  • Modeling battery packs
  • Adding thermal fidelity to battery models
  • Design supervisory control logic for battery operation
  • Perform State-Of-Charge estimation and cell balancing
  • Compute current limits and design fault diagnostic system
  • Closed-loop simulation of battery pack with battery management system

Day 1 of 2


Getting Started with a Battery Cell

Objective: Define terms used in a battery component. Construct a charging circuit to simulate the CC-CV charging of the cell.

  • Define battery terms (cell capacity, C-rate, open circuit voltage)
  • Model battery characteristics using the Battery(table-based) block
  • Construct charge and discharge circuit with Simscape™

Cell Characterization

Objective: Analyze the equivalent circuit model of a cell. Perform characterization of a given cell.

  • Equivalent circuit model of a Battery block
  • Overview of parameter estimation
  • Perform cell characterization

Battery Pack Modeling

Objective: Connect characterized cells in series configuration to create battery packs. Create thermal environment to perform multi-domain system level simulation

  • Create battery modules
  • Model cell degradation and cell inconsistencies
  • Model cell thermal effects using Simscape™
  • Add thermal fidelity to the battery module

Day 2 of 2


Battery Management System

Objective: Introduction to battery management system. Develop supervisory control scheme for efficient and safe battery pack operation.

  • Overview of a battery management system
  • Design requirements and constraints
  • Design Stateflow® logic to charge a cell using CC-CV control scheme
  • Design supervisory control logic of battery management system using Stateflow®
  • Create test scenarios for battery management system using Simulink Test™

State of Charge Estimation

Objective: Estimate state of charge (SoC) of a cell. Balance charge levels using a passive cell balancing scheme.

  • Estimate the cell's state of charge using coulomb counting
  • Estimate the cell's state of charge using extended Kalman Filter
  • Implement a passive cell balancing network using Simscape™ and Stateflow®

Fault Monitoring and Current Limit Computation

Objective: Compute battery pack's charging and discharging current limits that satisfy design constraints and detect faults during pack operation.

  • Detect over-voltage/over-current, short circuit, under-voltage/under-current faults during battery operation
  • Compute current limits for host application
  • Closed-loop simulation of battery pack with battery management system

Appendix A: Kalman Filter and Extended Kalman Filter

Objective: Use Kalman Filter and Extended Kalman filter blocks from Control System Toolbox™ library to perform state estimation.

  • Estimate states of discrete-time or continuous-time linear system using Kalman filter
  • Estimate states of discrete-time nonlinear system using extended Kalman filter

Level: Intermediate

Prerequisites:

  • Fundamental knowledge of Simulink, Stateflow and Simscape

Duration: 2 days

Languages: English, 日本語, 中文