Different Electric Vehicles (EV) types have beenrecently developed with the aim of solving pollution problemscaused by the emission of gasolinepowered engines.Environmental Considerations promote the adoption 01 EV forurban transportation. As it is well known one of the weakestpoints ofelectric vehicle is the battery system. Vehicle autonomyand therefore accurate detection of battery state of charge areamong the main drawbacks that prevent he spread of electricvehicles in the consumer market.This paper deals with the analysis of battery state of charge:performances of B few sizes of batteries are analyzed and theirstate of charge is estimated with a Neural Network (NN) baredsystem. The obtained results have been used to design a ion.lithium battery pack suitable lor electric vehicles. The proposedSystem presents high capability of energy recovering in brakingconditions, together with charge equalization, over and undervoltage protection. Moreover a Neural Network basedestimation of battery state of charge has been implemented inorder to optimize autonomy instead of perfarmanas or viceversadepending on journey.
EV Battery State of Charge: Neural Network Based Estimation / Affanni, A.; Concari, C.; Franceschini, G.; Lorenzani, Emilio; Tassoni, C.; Bellini, Alberto. - In: INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY. - ISSN 1229-9138. - ELETTRONICO. - 2:(2003), pp. 684-688. (Intervento presentato al convegno IEEE International Electric Machines and Drives Conference, IEMDC 2003 tenutosi a Wisconsin, USA nel June 1-4 2003) [10.1109/IEMDC.2003.1210310].