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ZEBRA battery SOC estimation using PSO-optimized hybrid neural model considering aging effect

Davood Gharavian, Reza Pardis, Mansour Sheikhan
2012 IEICE Electronics Express  

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The state of charge (SOC) estimation for electric vehicles (EVs) is important and helps to optimize the utilization of the battery energy storage in EVs. In this way, aging is also a key parameter impacting the performance of batteries. In this paper, a hybrid neural model is proposed for the SOC estimation of ZEBRA (Zero Emission Battery Research Activities) battery considering the aging effect through the state of health (SOH) and the discharge efficiency (DE) parameters. The number of hidden
more » ... nodes in neural modules is also optimized using particle swarm optimization (PSO) algorithm. The SOC estimation error of the proposed system is 1.7% when compared with the real SOC obtained from a discharge test.
doi:10.1587/elex.9.1115 fatcat:voxuqlk64vc2rd74tesjapdywu
Citation

Davood Gharavian, Reza Pardis, Mansour Sheikhan. "ZEBRA battery SOC estimation using PSO-optimized hybrid neural model considering aging effect." IEICE Electronics Express 9.13 (2012) 1115-1121