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

• Published in: Energies (Basel) Vol. 16; no. 16; p. 5887
• Main Authors: Naguib, Mina, Rathore, Aashit, Emery, Nathan, Ghasemi, Shiva, Ahmed, Ryan
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-08-2023
• Subjects: Accuracy; Batteries; battery management system; battery temperature; Electric vehicles; electrified vehicles; lithium-ion batteries; Parameter estimation; Parameter identification; Partial differential equations; Physics; Sensors; Temperature; Vehicles
• ISSN: 1996-1073; 1996-1073
• DOI: 10.3390/en16165887

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.