Ma, Zetao (Harbin Institute of Technology), Murgovski, Nikolce (Chalmers University of Technology), Cui, Shumei (Harbin Institute of Technology)

Predictive Energy Managementfor Electric Variable Transmission HEV

Scheduled for presentation during the Regular Session "Modeling & Control: Powertrain" (WeAT2), Wednesday, June 26, 2019, 11:50−12:10, Chenonceau

9th IFAC International Symposium on Advances in Automotive Control, June 23-27, 2019, Orléans, France

This information is tentative and subject to change. Compiled on April 23, 2024

Abstract

This paper introduces predictive energy management for the hybrid electric powertrain with an electric variable transmission. First of all, optimization of the energy management in hybrid mode is separated into a bi-level program, in which one static level optimizes the engine speed of a compound unit consists of the engine and electric variable transmission (EVT), another dynamic level optimizes the power split between the compound unit and the battery using equivalent consumption minimization strategy (ECMS). Moreover, combining ECMS with dynamic programming (ECMS-DP), engine on/o control is also taken into account by iteratively updating the costate. Finally, the ecient ECMS-DP optimization is incorporated into the framework of model predictive control (MPC) and solved for each predictive horizon. Computation eciency and optimization results are presented by simulation.