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11.11.14 KB. Ok to add accepted version to spiral, subject to 12 months embargo (published online 21 Sept 2014

Abstract-Supervisory control systems (SCSs) are used to manage the powertrain of hybrid electric vehicles (HEV). This paper presents a novel SCS called Exclusive operation strategy (XOS) that applies simple rules based on the idea that batteries are efficient at lower loads while engines and generators are efficient at higher loads. The XOS is developed based on insights gained from three conventional SCSs for series HEVs: Thermostat control strategy (TCS), Power follower control strategy (PFCS) and Global equivalent consumption minimization strategy (GECMS). Also, recent technological developments have been considered to make the XOS more suited to modern HEVs than conventional SCSs. The resulting control decisions are shown to emulate the operation of approximate global optimal solutions and thus achieve significant improvement in fuel economy as compared to TCS and PFCS. In addition, the generally linear relationship between required power and engine power for the XOS provides auditory cues to the driver that are comparable to conventional vehicles, thus reducing barriers to adopting HEVs. The simplicity and effectiveness of the XOS makes it a practical SCS.

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This paper introduces a simulation model that can be used to develop and test designs and control systems for hybrid electric vehicles (HEVs). The work involves a novel simulating platform, developed in Simulink, where each component of a series HEV is developed using a first-principles approach in a modular fashion, validated by available experimental data and then integrated to form a coupled nonlinear dynamic model. The vehicle model is capable to act as a platform for the design of supervisory control systems (SCSs) that optimize the energy flow in the powertrain. Simulations with two distinct SCSs and two driving cycles are used to analyze the vehicle performance under varying driving and operating conditions. The results demonstrate the applicability of the model for realistic prediction of both vehicle behavior and component energy losses, design optimization and control system design.

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