Stochastic Optimal Control of Parallel Hybrid Electric Vehicles
AbstractEnergy management strategies (EMSs) in hybrid electric vehicles (HEVs) are highly related to the fuel economy and emission performances. However, EMS constitutes a challenging problem due to the complex structure of a HEV and the unknown or partially known driving cycles. To meet this problem, this paper adopts a stochastic dynamic programming (SDP) method for the EMS of a specially designed vehicle, a pre-transmission single-shaft torque-coupling parallel HEV. In this parallel HEV, the auto clutch output is connected to the transmission input through an electric motor, which benefits an efficient motor assist operation. In this EMS, demanded torque of driver is modeled as a one-state Markov process to represent the uncertainty of future driving situations. The obtained EMS has been evaluated with ADVISOR2002 over two standard government drive cycles and a self-defined one, and compared with a dynamic programming (DP) one and a rule-based one. Simulation results have shown the real-time performance of the proposed approach, and potential vehicle performance improvement relative to the rule-based one. View Full-Text
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Qin, F.; Xu, G.; Hu, Y.; Xu, K.; Li, W. Stochastic Optimal Control of Parallel Hybrid Electric Vehicles. Energies 2017, 10, 214.
Qin F, Xu G, Hu Y, Xu K, Li W. Stochastic Optimal Control of Parallel Hybrid Electric Vehicles. Energies. 2017; 10(2):214.Chicago/Turabian Style
Qin, Feiyan; Xu, Guoqing; Hu, Yue; Xu, Kun; Li, Weimin. 2017. "Stochastic Optimal Control of Parallel Hybrid Electric Vehicles." Energies 10, no. 2: 214.
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