A robust online energy management strategy for fuel cell/battery hybrid electric vehicles. (18th May 2020)

• Record Type: Journal Article
• Authors: Wu, Jinglai; Zhang, Nong; Tan, Dongkui; Chang, Jiujian; Shi, Weilong
• Is Part Of: International journal of hydrogen energy. Volume 45:Number 27(2020)
• Page Start: 14093
• Page End: 14107
• Publication Date: 2020-05-18
• Subjects: Fuel cell -- Hybrid electric vehicles -- Online energy management strategy -- Robustness -- Uncertainty; Hydrogen as fuel -- Periodicals; Hydrogène (Combustible) -- Périodiques; Hydrogen as fuel; Periodicals; 665.81
• DOI: 10.1016/j.ijhydene.2020.03.091
• Languages: English
• ISSNs: 0360-3199

Abstract

Abstract: Traditional optimization-based energy management strategies (EMSs) do not consider the uncertainty of driving cycle induced by the change of traffic conditions, this paper proposes a robust online EMS (ROEMS) for fuel cell hybrid electric vehicles (FCHEV) to handle the uncertain driving cycles. The energy consumption model of the FCHEV is built by considering the power loss of fuel cell, battery, electric motor, and brake. An offline linear programming-based method is proposed to produce the benchmark solution. The ROEMS instantaneously minimizes the equivalent power of fuel cell and battery, where an equivalent efficiency of battery is defined as the efficiency of hydrogen energy transforming to battery energy. To control the state of charge of battery, two control coefficients are introduced to adjust the power of battery in objective function. Another penalty coefficient is used to amend the power of fuel cell, which reduces the load change of fuel cell so as to slow the degradation of fuel cell. The simulation results indicate that ROEMS has good performance in both fuel economy and load change control of fuel cell. The most important advantage of ROEMS is its robustness and adaptivity, because it almost produces the optimal solution without changing the control parameters when driving cycles are changed. Highlights: An optimization-based online EMS for FCHEVs is proposed. A linear programming-based EMS is presented to produce the reference solution. The load change control of fuel cell slows the degradation of fuel cell stack. Robustness of the proposed online EMS to uncertain conditions of driving cycles.