Configuration, design, and optimization of air-cooled battery thermal management system for electric vehicles: A review

Abstract

A battery thermal management system (BTMS) is arguably the most vital component of an electric vehicle (EV), as it is responsible for ensuring the safe and consistent performance of lithium ion batteries (LiB). LiBs are considered one of the most suitable power options for an EV drivetrain. Owing to lithium's atomic number of three (3) and it being the lightest element of the metals, lithium is able to provide fantastic energy-to-weight characteristics for any lithium-based battery. LiBs are also known for having low self-discharging properties and hence provide long life cycle operation. To obtain a maximum power output from LiBs, it is necessary to critically monitor the operating conditions of LiBs, particularly temperature, which is known to directly affect the performance and life of LiBs. The temperature rise present around LiBs is caused by the heat generation phenomena of lithium ion cells during charge and discharge cycles. In this study, an investigation is made into one of the major categories of a BTMS, used in making the EV powertrain much more efficient and safe. Specifically, this study investigates and reviews air-cooled BTMS techniques (passive and active) and design parameter optimization methods (either via iteration or algorithms) for improving various BTMS design objectives. In particular, this study investigates minimizing the change in temperature among cells (Delta T-max) in a battery pack (BP). The data are classified, and results from recent studies on each method are summarized. It is found that despite features such as extreme simplicity, ease of implementation, and the relatively low cost of naturally air-cooled BTMS, it is almost impossible for the methods to provide adequate cooling conditions for the high energy density LiBs used in EVs. A shift in focus from a naturally air-cooled BTMS to a forced air-cooled BTMS is observed from the amount of studies found on the topics during the time scope of this study. Parameter configuration optimization techniques for the air-cooled BTMS are discussed and classified, and optimization algorithms applied by researchers to improve objectives of the BTMS are identified.