Battery modelling and state of charge estimation methods for Energy Management in Electric Vehicle-A review
Srinivas Singirikonda, Y. P. Obulesu
Abstract
Abstract To reduce global warming, the Electric Vehicles (EV) are more attracting Worldwide for replacement of conventional IC engine vehicle but the main problem is driving range and the cost of EV is very high compared to a conventional vehicle. The driving range is mainly depending on the type of battery and size of the battery pack used in EV, for long driving range more number of batteries are required which automatically increase the weight and cost of EV. An effective battery management system will increase battery life and driving range of the EV with less number of batteries. In battery management system of EV the battery is major component but battery is costly and managing power of the battery is very much essential in EV technology. Majority of the issues can be solved by developing advanced battery management system (BMS) in EV such as, Battery modelling, accurate battery state of charge and state of health estimation, which can provide an exact driving range of EV and charging/discharging strategies work more effectively. This review paper mainly focuses on different battery modelling techniques and existing battery SOC estimation methods, issues and challenges.