Battery Management Systems Laboratory (BMSLab)

University of Windsor, Windsor, Ontario
What the facility does

Improves the safety, lifespan and reliability of batteries for electric vehicles, electronics and energy storage.

Areas of expertise

The Battery Management Systems Laboratory develops methods to estimate battery charge, assess battery health and predict remaining useful life. Combining laboratory testing, data analysis and artificial intelligence, it studies battery performance under real operating conditions, with applications in portable electronics, electric vehicles and large-scale energy storage.

Its expertise includes estimating remaining charge and driving range throughout battery life; assessing used batteries for sorting, refurbishment and second-life applications; modelling electrical and thermal behaviour; and developing charging and thermal-management strategies that balance charging speed, temperature and battery degradation. The laboratory’s work includes patented battery fuel-gauging methods and widely cited research on battery characterization. It also develops portable diagnostic tools for rapid battery health assessment, including methods that measure a battery’s electrical response without disassembly.

Research services

The Battery Management Systems Laboratory offers the following services through collaborative research projects:

  • Battery characterization: Characterize battery cells and modules to measure capacity, internal resistance, voltage behaviour and impedance at different temperatures.
  • Battery health and life assessment: Assess the health and remaining life of new, used and second-life batteries.
  • Battery charge, health and range estimation: Develop and validate methods to estimate battery charge, health and driving range using laboratory and field data.
  • Battery management system evaluation: Evaluate and benchmark battery management system software and hardware, including hardware-in-the-loop testing.
  • Battery modelling: Build electrical and thermal battery models to support battery pack design, sizing and cooling.
  • Battery data analysis: Analyze field and fleet battery data with physics-informed machine learning to detect battery degradation and faults early.
  • Charging and cell balancing: Design strategies to shorten charging time while limiting heat and battery wear.
  • Training: Train students and industry staff in battery management, testing and data analysis.
Sectors of application
  • Automotive
  • Clean technology
  • Consumer durables
  • Energy
  • Transportation
  • Battery cycling and characterization: Charge and discharge battery cells and modules under programmable current and voltage profiles to measure capacity, efficiency and ageing.
  • Impedance measurement: Measure battery impedance across a range of frequencies to assess internal resistance and health without disassembly.
  • Temperature-controlled testing: Test batteries at controlled temperatures to assess thermal behaviour, safety and ageing.
  • Battery management system validation: Test battery management hardware and software against simulated battery packs using hardware-in-the-loop systems.
  • On-site battery diagnostics: Assess battery health on site using a portable diagnostic platform for electric vehicle modules and consumer devices.
  • Data analysis and modelling: Analyze laboratory and field data to develop battery models using dedicated computing workstations and specialized modelling, simulation, and machine learning tools (MATLAB/Simulink and Python).
  • Gates Corporation (United States)
  • Automotive Parts Manufacturers' Association (APMA)