Battery management system for electric vehicle and drone application


Fire hazard in electric vehicle is one of the key problem that requires immediate attention. One of the way to prevent such fires in battery systems is have a competent battery management system which can predict the potential failure of the battery pack. Battery management system (BMS) consists of battery model, parameters and state estimation algorithms and optimziation toolboxes. Traditionally, circuit based models are being used in these BMS which do not provide physical understanding of the battery systems. In order to have accurate predictions from these BMS, detailed models utilizing electrochemical engineering priciples are being used.

This PhD topic relates to developing a battery management system consisting of electrochemical models which will be capable of estimating the states and parameters of battery system. For example, such states and parameters can represent the state of charge, state of power and state of health. Incorporating such models in BMS will increase the predicability and ensure safe and efficient battery operation. 

Similar to fire hazard, the drone battery system requires very accurate infomration on the remaining power (remanining flight time) so that the intended operations (like spying in enemy territory) can be done reliably. For such critical operations, accurate battery modeling and state estimation are essential. 

The project will have both the components: modeling (Matlab/Python/Maple) and expeirments (Charging discharging of battery systems using optimal charging discharging conditions).

Knowledge of transport phenomena and reaction engineering will be very helpful. 


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