Development of Robust State of Charge Estimation Algorithms for Lithium-ion Batteries in Electric Vehicles
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With increasing innovation and environmental awareness, electric vehicles (EVs) are becoming more popular than the conventional fuel based vehicles for emission-free future transportation. Lithium-ion battery (LIB) is the most suitable choice of energy storage system that works as the core of an EV. Along with the battery, a micro-controller known as battery management system (BMS) is required for reliable and secure operation of the battery. In BMS, real-time access to the information of one of the most critical battery states, known as state of charge (SOC), is vital as it indicates the remaining capacity of the battery, helps to prevent overcharging and undercharging, increases capacity utilization and lifespan, improves reliability, reduces cost, and ensures safety of the battery and its surroundings. Being an internal state, SOC is not available for direct measurement by any sensor and estimating it accurately for an LIB is non-trivial due to the highly nonlinear nature of the battery and various uncertain operating conditions. The literature reports several different approaches to estimate SOC of an LIB with each having its own advantages and drawbacks. It is important to note that each method of SOC estimation in literature possess some drawbacks either in accuracy or in real-time implementation. Hence, there is a scope for further improvement of these methods to enhance the performance of SOC estimation.
Supervisors: Majhi, Somanath and Nayak, Sisir Kumar
Lithium-ion Battery, Electric Vehicle, State of Charge Estimation, Sliding Mode Observer, Relay Feedback, Recursive Least Square Approach, System Identification