Competitive Evaluation of Energy Management Strategies for Hybrid Electric Vehicle Based on Real World Driving

Abstract

Global warming, the decline of oil resources as well as the introduction of emission regulations have led to a research focus in new drive technologies. Within this group of alternative drive technologies, fuel cell hybrid electric vehicles (FHEV) are considered to be especially effective. Nevertheless, in order to achieve an efficient operation, an energy management system (EMS) is required. Since system efficiency as well as the operation characteristics is determined by the chosen EMS scheme, current research focuses on new EMS approaches. This paper reviews and evaluate three widely accepted state of the art EMS schemes: classical proportional-integral control, state machine approach and online optimization based equivalent consumption minimization strategy (ECMS). The evaluation is done based on an a physical model of a FHEV. Since, use cases of the vehicle also have significant influence, real word driving was used to generate test cases. Thus, a method to cluster recorded driving data with regards to drive scenarios is proposed. Finally, the extracted reference cycles in combination with the physical model form a virtual test bench, used to evaluate the three EMS approaches under test.