Energy management of plug-in hybrid electric vehicles with unknown trip length

This paper proposes a novel control strategy for plug-in hybrid electric vehicles (PHEV). The minimization of the utility factor weighted fuel consumption (FCUFW), which represents the average fuel consumption in numerous trips, is firstly proposed as the objective of the energy management. In previous studies, the trip length is usually assumed to be known. Then, if it is shorter than the all-electric range (AER), a Charge Depleting Charge Sustaining (CDCS) strategy leads to the minimum fuel consumption; otherwise, a blended strategy that spends down battery energy almost uniformly brings the minimum fuel consumption. Nevertheless, the trip length is not always known before trip in real life. To deal with the cases of unknown trip length, this paper proposes a Range ADaptive Optimal Control (RADOC) strategy to minimize the FCUFW, which utilizes the statistical information of the trip length. The RADOC strategy was verified by dynamic programming and was found to be somewhere in between the blended and CDCS strategies. Depending on the nature of the trips, the RADOC strategy was found to improve FCUFW between 0.10% and 4.07% compared with the CDCS strategy. The RADOC strategy is very close to the CDCS strategy when the PREY is used in regular daily driving. On the contrary, the RADOC solution exhibits a uniform battery discharging behavior similar to the blended strategy for urban utility vehicles or taxis. The behavior of the RADOC strategy is also studied for different battery sizes and driving cycles. (C) 2014 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.