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An Online Fuel Consumption and Emission Reduction Power Management Strategy for Plug-in Hybrid Electric Vehicles

An Online Fuel Consumption and Emission Reduction Power Management Strategy for Plug-in Hybrid... Abstract An online power management strategy (PMS) for plug-in hybrid electric vehicles is presented in this paper. This PMS with the capability to reduce both the fuel consumption and the emission, has simple mathematics and excludes a priori knowledge of the driving cycle. The only required information is the driving duration that can be estimated by the driver or by the vehicle information systems, so the proposed method can be easily implemented. Furthermore, an adaptive form of this PMS is presented and its performance is compared with other strategies. Using the online adaptive PMS method, the incoming driving cycle condition is predicted by the vehicle past conditions. In this paper, the engine fuel characteristics are linearized to several zones. At any instant, one of these zones is selected for the engine operation. In each zone, an optimal cost function is minimized for the fuel consumption and the emission reduction. Moreover, different cost functions are defined and used on various engines. Finally, the proposed PMS is simulated in the ADVISOR environment and compared with conventional method. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Vehicle Engineering Science and Engineering Publishing Company

An Online Fuel Consumption and Emission Reduction Power Management Strategy for Plug-in Hybrid Electric Vehicles

Vehicle Engineering , Volume 1 (2) – Jun 1, 2013

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Publisher
Science and Engineering Publishing Company
Copyright
Science and Engineering Publishing Company
ISSN
2328-1677
eISSN
2328-1669

Abstract

Abstract An online power management strategy (PMS) for plug-in hybrid electric vehicles is presented in this paper. This PMS with the capability to reduce both the fuel consumption and the emission, has simple mathematics and excludes a priori knowledge of the driving cycle. The only required information is the driving duration that can be estimated by the driver or by the vehicle information systems, so the proposed method can be easily implemented. Furthermore, an adaptive form of this PMS is presented and its performance is compared with other strategies. Using the online adaptive PMS method, the incoming driving cycle condition is predicted by the vehicle past conditions. In this paper, the engine fuel characteristics are linearized to several zones. At any instant, one of these zones is selected for the engine operation. In each zone, an optimal cost function is minimized for the fuel consumption and the emission reduction. Moreover, different cost functions are defined and used on various engines. Finally, the proposed PMS is simulated in the ADVISOR environment and compared with conventional method.

Journal

Vehicle EngineeringScience and Engineering Publishing Company

Published: Jun 1, 2013

Keywords: Adaptive Control; Fuel Consumption and Emission Reduction; Plug-in Hybrid Electric Vehicle; Power Management Strategy

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