Robust Electro-Thermal Modeling of Lithium-Ion Batteries for Electrified Vehicles Applications

Mina Naguib (), Aashit Rathore, Nathan Emery, Shiva Ghasemi and Ryan Ahmed
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Mina Naguib: Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON L8S 4L8, Canada
Aashit Rathore: Department of Mechanical Engineering, McMaster University, Hamilton, ON L8S 4L8, Canada
Nathan Emery: Department of Mechanical Engineering, McMaster University, Hamilton, ON L8S 4L8, Canada
Shiva Ghasemi: Department of Mechanical Engineering, McMaster University, Hamilton, ON L8S 4L8, Canada
Ryan Ahmed: Department of Mechanical Engineering, McMaster University, Hamilton, ON L8S 4L8, Canada

Energies, 2023, vol. 16, issue 16, 1-20

Abstract: Lithium-ion battery (LIBs) packs represent the most expensive and safety-critical components in any electric vehicle, requiring accurate real-time thermal management. This task falls under the battery management system (BMS), which plays a crucial role in ensuring the longevity, safety, and optimal performance of batteries. The BMS accurately monitors cell temperatures and prevents thermal runaway by leveraging multiple temperature sensors; however, adding a temperature sensor to each individual cell is not practical and increases the total cost of the EV. This paper provides three key original contributions: (1) the development and optimization of a new efficient electro-thermal battery model that accurately estimates the LIB voltage and temperature, which reduces the required number of temperature sensors; (2) the investigation of the ECM parameters’ dependency on the state of charge (SOC) at a wide range of ambient temperatures, including cold temperatures; (3) the testing and validation of the proposed electro-thermal model using real-world dynamic drive cycles and temperature ranges from −20 to 25 °C. Results indicate the effectiveness of the proposed electro-thermal model, which shows good estimation accuracy with an average error of 50 mV and 0.5 °C for the battery voltage and surface temperature estimation, respectively.

Keywords: battery temperature; battery management system; electrified vehicles; lithium-ion batteries (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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