EV battery state of charge: neural network based estimation

Different Electric Vehicles (EV) types have been recently developed with the aim of solving pollution problems caused by the emission of gasoline-powered engines. Environmental considerations promote the adoption of EV for urban transportation. As it is well known one of the weakest points of electric vehicle is the battery system. Vehicle autonomy and therefore accurate detection of battery state of charge are among the largest resistance for a common introduction of electric vehicles in the consumer market. This paper deals with the analysis of battery state of charge: a few types of batteries are analyzed and compared, and their state of charge is estimated with a neural network based system. The obtained results have been used to design a ion-lithium battery pack suitable for electric vehicles: high capability of energy recovering in braking conditions, charge equalization, over and under voltage protection and obviously state of charge information in order to optimize autonomy instead of performances or vice-versa depending on journey.