Stochastic Optimal Control of Parallel Hybrid Electric Vehicles

Abstract

Energy 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.

An Online Energy Management Control for Hybrid Electric Vehicles Based on Neuro-Dynamic Programming

“…Tables 3-5 show the fuel economy and component efficiency of SDP, and the proposed NDP-based EMS in driving cycles of CYC_UDDS, CYC_1015, and the composite driving cycle. We can conclude that, compared with the SDP in [6], the proposed NDP EMS improves fuel economy by about 25.9%, 6.2%, and 25.6%, respectively, under CYC_UDDS, CYC_1025, and the composite driving cycle. In the three driving cycles, the proposed NDP and SDP all keep SOC in nearly the same range.…”

“…We have compared the proposed NDP method with the NDP method in [14] to test the proposed NDP based on CWNN and MRWNN. We have also compared the NDP EMS with a SDP method proposed in [6], which is an optimal method, in driving cycles of CYC_UDDS, CYC_1015 and a composite driving cycle, which is composed of a CYC_1015, a CYC_UDDS, and a CYC_WVUCITY driving cycle, to test the optimality of the proposed NDP method.…”

“…Here, a vehicle control unit directly commands the torque required from both power sources of the vehicle. The powertrain information has been shown in [6]. …”

“…Secondly, the optimal EMS problem is demonstrated in Section 2.2, which introduces the HEV modeling, key concepts of the EMS control problem, and instantaneous cost in optimization, which have been described in [6]. We present the preparation of knowledge for the proposed NDP method, which contains a wavelet transformation theory, in Section 2.3; a CWNN in Section 2.4; a multi-resolution analysis theory of a function in Section 2.5; and a multi-resolution wavelet neural network in Section 2.6.…”

Study of the Energy Conversion Process in the Electro-Hydrostatic Drive of a Vehicle

“…The constants K E p , T E i define the settings of the PI current controller. It was assumed, that in the considered converter, voltage U 2 powering the motor may not exceed the voltage of the battery U 1 , which was described in the Formulae (13).…”