E-COSM 2021 Paper Abstract

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Paper MoAT3.3

Wang, Muyao (Beijing Institute of Technology), Yang, Chao (Beijing Institute of Technology), Wang, Weida (Beijing Institute of Technology), Chen, Ruihu (Beijing Institute of Technology), Li, Ying (Beijing Institute of Technology)

A Power Distribution Strategy for Heavy Duty HEV with Series Hybrid Powertrain Based on Model Predictive Control Method

Scheduled for presentation during the Invited session "Advanced Powertrain Control" (MoAT3), Monday, August 23, 2021, 14:40−15:00, Room T3

6th IFAC Conference on Engine and Powertrain Control, Simulation and Modeling, August 23-25, 2021, Tokyo, Japan

This information is tentative and subject to change. Compiled on March 28, 2024

Keywords Engine Control, Powertrain Control, Control Design

Abstract

Aiming at the problem of power distribution strategy of heavy-duty HEV with series hybrid powertrain, this paper proposed a power distribution strategy based on model predictive control (MPC). The strategy establishes the related energy consumption index and the physical constraints of the whole vehicle. It predicts the power and speed of vehicle powertrain in a given prediction time domain and distributes generator power and motor power reasonably according to the demand power. In order to reduce the computation of solving quadratic programming subproblems, the improved sequential quadratic programming (ISQP) algorithm is involved to solve the rolling horizon optimization problem. To prove the effectiveness of the strategy, the simulation is carried out under a given condition. The simulation results show that the strategy has better fuel economy than the rule-based strategy under the given condition.

 

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