Battery state-of-charge estimation based on fuzzy neural network and improved particle swarm optimization algorithm

Proceedings of the 2012 2nd International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2012

Volumn , Issue , 2012, Pages 22-27

  Lv, Jianxun ^a   Yuan, Haiwen ^a   Lv, Yingming ^a  

^a BEIHANG UNIVERSITY   (China)

Author keywords

Battery; Estimation; Fuzzy neural network; Improved particle swarm optimization algorithm; State of charge

Indexed keywords

ACCURATE ESTIMATION; BATTERY; BATTERY LOADS; BATTERY MANAGEMENT; BATTERY SURFACE TEMPERATURES; DISCHARGE CURRENTS; EFFECTIVE APPROACHES; ESTIMATION APPROACHES; FNN MODELS; GENERALIZATION CAPACITY; HEURISTIC OPTIMIZATION TECHNIQUE; HYBRID ALGORITHMS; IMPROVED PARTICLE SWARM OPTIMIZATION ALGORITHMS; IMPROVED PSO ALGORITHMS; INITIAL VALUES; LITHIUM-ION BATTERY; MODEL-BASED OPC; PARTICLE SWARM OPTIMIZATION ALGORITHM; STATE OF CHARGE; STATE-OF-CHARGE ESTIMATION; TERMINAL VOLTAGES; TRAINING ACCURACY; TRAINING METHODS;

ATMOSPHERIC TEMPERATURE; COMMUNICATION; FUZZY NEURAL NETWORKS; GENETIC ALGORITHMS; MATHEMATICAL MODELS; MEASUREMENTS; REACTIVE POWER;

ESTIMATION;

EID: 84874431743     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IMCCC.2012.13     Document Type: Conference Paper

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