Volume 13, Issue 4 (Journal of Control, V.13, N.4 Winter 2020)                   JoC 2020, 13(4): 1-14 | Back to browse issues page

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Hassanzade M, Rahmani Z. Improving the Energy Management of Parallel Hybrid Electric Vehicle by Dynamic Programming Using Electro-Thermal Model of Battery. JoC 2020; 13 (4) :1-14
URL: http://joc.kntu.ac.ir/article-1-570-en.html
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Abstract:   (6717 Views)
In this paper, an offline energy management system (EMS) is proposed for parallel hybrid electric vehicles (HEVs). The proper energy management system is necessary for dividing torque between electrical motor and Internal Combustion Engine (ICE). The battery is a crucial component of hybrid electric vehicles and affects significantly the cost and the performance of the whole vehicle. The primary factors accelerating battery aging are high temperatures and high states of charge (SOC) of the battery. SOC is the most important state variable in EMS, and usually considered as the only dynamic variable in past researches, but the battery temperature is often considered to be constant for simplicity and the effects of EMS on the temperature variations are neglected. In this paper, first, dynamic programming is applied to a parallel HEV without considering variation of the temperature of the battery. Then, the model of battery is improved by modelling the cooling system to take into account temperature variations and show how neglecting thermal dynamics of the battery in EMS is impractical. Finally, by integrating the battery temperature as a state variable in the optimization problem, a new energy management strategy controlling variations of the battery temperature and SOC is proposed. The simulation results on tested vehicle show that in the proposed method charge and temperature of the battery is controlled so that the proposed EMS method prevents uncontrolled variations of the battery temperature and reduces the degradation rate of it.
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Type of Article: Research paper | Subject: Special
Received: 2018/03/18 | Accepted: 2018/07/22 | Published: 2020/01/30

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