Development of Test-Bed Controller for Powertrain of HEV
Peng Liu,
Zhenhua Jin,
Yuwei Hua and
Lu Zhang
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Peng Liu: State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
Zhenhua Jin: State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
Yuwei Hua: State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
Lu Zhang: State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
Energies, 2020, vol. 13, issue 13, 1-19
Abstract:
The dynamic test-bed is a powerful tool for the powertrain integration and control strategy development of a hybrid electric vehicle (HEV). This paper focuses on developing a test-bed controller with driver simulation, road load simulation (RLS), and engine simulation. The main factors that influence the RLS accuracy are analyzed, especially inertia of test-bed and torque signal sampling frequency, and the RLS algorithm with penalty function based on a forward model is proposed. The engine model is developed and permanent magnet synchronous motor (PMSM) is adopted to realize engine start-up/stop, torque control, and inertia simulation. The simulation platform was built in MATLAB/Simulink to verify its accuracy. The simulation results present the developed RLS with a penalty function based on a forward model that can reduce the speed and torque error. The developed controller is applied to the single-axis parallel HEV test-bed. The experiment results show that the developed test-bed controller can precisely emulate the road load and improve the efficiency of the development of HEV powertrain.
Keywords: hybrid electric vehicle; test-bed controller; road load simulation; penalty function; Engine simulation (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: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:13:y:2020:i:13:p:3372-:d:379039
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