Thermal Modeling and Optimization of Lithium-Ion Batteries for Electric Vehicles

This dissertation contributes to the modeling and optimization of Lithium-ion battery’s thermal management for electrified vehicles (EVs). EVs in automotive technology is one of the principal solutions to today’s environmental concerns such as air pollution and greenhouse impacts. Light duty and heavy duty EVs can decrease the amount of the pollution efficiently. EV’s receive their power from installed rechargeable batteries in the car. These batteries are not just utilized to power the car but used for the functioning of lights, wipers and other electrical accessories. The Lithium-ion batteries (LIBs) have attracted a lot of research interest in recent years, due to their high potential as compared to the conventional aqueous based batteries, high gravimetric and volumetric energy density, and high power capability. However, Li-ion batteries suffer from high self-heating, particularly during high power applications and fast charging, which confines their lifetime and cause safety, reliability and environmental concerns. Therefore, the first part of this study consists of the experimental investigation of the charge-discharge behavior and heat generation rate of lithium ion cells at different C-rates to monitor and record the thermal behavior of the cell. A further concern regarding LIBs is strongly dependent on the quality and efficiency of battery thermal management system. Hence, this is extremely important to identify a reliable and accurate battery management system (BMS). Here in the second part, we show that thermal management and the reliability of Li-ion batteries can be drastically improved using optimization technique. Furthermore, a LIB is a compact system including high energy materials which may undergo thermal runaway and explode the battery if overcharged due to the decomposition of battery materials within the electrolyte and electrodes that generate flammable gaseous species. The application of this kind of technology needs many laboratory experiments and simulations to identify the fundamental thermal characteristics of the system before passing it to the real use. An accurate battery model proposes a method to simulate the complex situations of the system without performing time consuming actual tests, thus a reliable scheme to identify the source of heat generation and required parameters to optimize the cell performance is necessary. For this reason, the latest phase of this research covers the development and comparison of a model based on adjustable design parameters to predict and optimize battery performances. This kind of model provides a relationship with the accuracy and simplicity to estimate the cell dynamics during charge and discharge