Optimal Cell Balancing Mechanism for Electric Vehicle
Electric vehicles (EVs) can help improve fuel economy, lower fuel costs, and reduce emissions. Lithium-ion (Li-ion) batteries are currently used in most EVs because of their high power-to-weight ratio, low self-discharge and high-energy efficiency. Cell balancing is a technique that improves battery life by maximizing the capacity of a battery pack with multiple cells in series. Cell balancing for the EVs is accomplished through either active or passive balancing but each one has its own challenges. This research is approached to overcome the limitation by having a trade-off between balancing speed and the power dissipation in the system. The key focus of this study is, research and experiment to balance the Li-ion battery pack with an effective algorithm to enhance the energy usage and life cycle of the battery by leveraging the active and passive concepts along with an appropriate Machine Learning (ML) based approach to meet the end application requirement. In order to find out an optimal algorithm considering various use case deployments, threshold has to be arrived between passive and active with the speed of balancing while managing the thermal challenges. The work is to analysing the battery parameters through Electro-chemical Impedance Spectroscopy (EIS) test methodology, realize a hardware for studying the balancing mechanism, model and simulate through Matlab/Simscape and optimize the behaviour through a ML based methodology. These experimented outcome and algorithms can be plugged into the Battery Management System (BMS) of the e-vehicle. This work is applicable in the e-vehicle industry segment whereby Li-ion batteries are extensively used.
Department of Electrical & Electronics Engineering, School of Engineering, Bengaluru campus
Machine Learning Techniques
Associate Professor,
Department of Electrical & Electronics Engineering,
School of Engineering,
Amrita Vishwa Vidyapeetham, Bengaluru
