A Novel Control Algorithm Design for Hybrid Electric Vehicles Considering Energy Consumption and Emission Performance

Yuan Qiao, Yizhou Song and Kaisheng Huang
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Yuan Qiao: State Key Laboratory of Automotive Safety and Energy, School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China
Yizhou Song: State Key Laboratory of Automotive Safety and Energy, School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China
Kaisheng Huang: State Key Laboratory of Automotive Safety and Energy, School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China

Energies, 2019, vol. 12, issue 14, 1-28

Abstract: Under the severe challenge of increasingly stringent emission regulations and constantly improving fuel economy requirements, hybrid electric vehicles (HEVs) have attracted widespread attention in the auto industry as a practicable technical route of green vehicles. To address the considerations on energy consumption and emission performance simultaneously, a novel control algorithm design is proposed for the energy management system (EMS) of HEVs. First, energy consumption of the investigated P3 HEV powertrain is determined based on bench test data. Second, crucial performance indicators of NOx and particle emissions, prior to a catalytic converter, are also measured and processed as a prerequisite. A comprehensive objective function is established on the grounds of the Equivalent Consumption Minimization Strategy (ECMS) and corresponding simulation models are constructed in MATLAB/SIMULINK. Subsequently, the control algorithm is validated against the simulation results predicated on the Worldwide-Harmonized Light-Vehicle Test Procedure (WLTP).Integrated research contents include: (1) The searching process aimed at the optimal solution of the pre-established multi-parameter objective function is thoroughly investigated; (2) the impacts of weighting coefficients pertaining to two exhaust pollutants upon the specific configurations of the proposed control algorithm are discussed in detail; and (3) the comparison analysis of the simulation results obtained from ECMS and classical Dynamic Programming (DP), respectively, is performed.

Keywords: hybrid electric vehicles; control algorithm design; energy consumption; emission performance (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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