Work

Stochastic Hybrid Model Predictive Control: Application to Parallel Hybrid Electric Vehicles

Year: 2023

Type: article

Abstract: Hybrid electric vehicles (HEVs) are attracting attention for their high fuel efficiency and low emissions compared to diesel-powered vehicles. The fuel efficiency of the HEV is highly dependent on the optimal power split ratio. The problem of finding the optimal power split ratio trajectory is difficult to solve with linear and/or deterministic controllers because it has nonlinear and stochastic characteristics. In this study, stochastic hybrid model predictive control (SHMPC) was applied to the HEV system. Piecewise affine (PWA) modeling of HEV systems was performed to model nonlinear systems with smaller model-plant mismatch compared to linear models. Furthermore, to account for the driver's stochastic behavior, a scenario-based stochastic model predictive control (SMPC) approach was employed. Controllers of scenario-based linear SMPC and scenario-based SHMPC are built. The controllers were tested in MATLAB/Simulink HEVP2 Reference Application simulation environment.

Source: IFAC-PapersOnLine

DOI: 10.1016/j.ifacol.2023.10.370

Authors: Hyun Min Park, Hyein Jung, Tae Hoon Oh, Se-Kyu Oh, Jong Min Lee

Institutions: Seoul National University, Kyoto University, Hyundai Motor Group (South Korea), Hyundai Motors (South Korea)

Language: English

Topic: Electric and Hybrid Vehicle Technologies

Subfield: Automotive Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure

Open Access status: diamond

OpenAlex ID: W4388918275

FWCI: 0.069

Cites: 13

Cited by: 1

Related to: 10