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Energies 2011, 4(8), 1178-1196;

Model Predictive Control-Based Fast Charging for Vehicular Batteries

Shenzhen Institutes of Advanced Technology, The Chinese Academy of Science, Shenzhen 518055, China
Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong, China
Department of Electrical Engineering, Tongji University, Shanghai 200092, China
Author to whom correspondence should be addressed.
Received: 13 June 2011 / Revised: 2 August 2011 / Accepted: 4 August 2011 / Published: 17 August 2011
(This article belongs to the Special Issue Electric and Hybrid Vehicles)
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Battery fast charging is one of the most significant and difficult techniques affecting the commercialization of electric vehicles (EVs). In this paper, we propose a fast charge framework based on model predictive control, with the aim of simultaneously reducing the charge duration, which represents the out-of-service time of vehicles, and the increase in temperature, which represents safety and energy efficiency during the charge process. The RC model is employed to predict the future State of Charge (SOC). A single mode lumped-parameter thermal model and a neural network trained by real experimental data are also applied to predict the future temperature in simulations and experiments respectively. A genetic algorithm is then applied to find the best charge sequence under a specified fitness function, which consists of two objectives: minimizing the charging duration and minimizing the increase in temperature. Both simulation and experiment demonstrate that the Pareto front of the proposed method dominates that of the most popular constant current constant voltage (CCCV) charge method. View Full-Text
Keywords: battery fast charging; model predictive control; state of charge; genetic algorithm; electric vehicles battery fast charging; model predictive control; state of charge; genetic algorithm; electric vehicles

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Yan, J.; Xu, G.; Qian, H.; Xu, Y.; Song, Z. Model Predictive Control-Based Fast Charging for Vehicular Batteries. Energies 2011, 4, 1178-1196.

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