MPC Based Optimal Energy Management of Electrical Vehicles with Hybrid Energy Storage on Fixed Routine

This article presents a model predictive control (MPC) based energy management strategy for electric vehicles powered by hybrid power sources, focusing on their performance improvements while running on fixed routines. The idea is to utilize the historic operation data to improve the energy allocation optimization solutions, with the goal of enhancing the energy efficiency of electric vehicles running on fixed driving routes by minimising losses through minimum battery current operations and extending the vehicles' driving range. Key contributions include the formulation of a model predictive control based energy allocation problem, and the implementation of convex hull constrained MPC based on historic data. Simulation results demonstrate the continual performance improvements in the presence of uncertainties being introduced into the system.

Authors

Institutions

Publication Details

Published
2025-06-18
DOI
https://doi.org/10.1109/itec63604.2025.11097959
Citations
1
Primary Topic
Electric and Hybrid Vehicle Technologies
Type
article
Field-Weighted Citation Impact
0.68
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

MPC Based Optimal Energy Management of Electrical Vehicles with Hybrid Energy Storage on Fixed Routine

Hanlin Lei, Kang Li, Benjamin Chong
1 citations
Electric and Hybrid Vehicle Technologies
0.68
article

MPC Based Optimal Energy Management of Electrical Vehicles with Hybrid Energy Storage on Fixed Routine

Hanlin Lei, Kang Li, Benjamin Chong
article en
1 citations

Abstract

This article presents a model predictive control (MPC) based energy management strategy for electric vehicles powered by hybrid power sources, focusing on their performance improvements while running on fixed routines. The idea is to utilize the historic operation data to improve the energy allocation optimization solutions, with the goal of enhancing the energy efficiency of electric vehicles running on fixed driving routes by minimising losses through minimum battery current operations and extending the vehicles' driving range. Key contributions include the formulation of a model predictive control based energy allocation problem, and the implementation of convex hull constrained MPC based on historic data. Simulation results demonstrate the continual performance improvements in the presence of uncertainties being introduced into the system.

University of Leeds (GB)
Affordable and clean energy
Openalex Percentile: Top 27%
Electric and Hybrid Vehicle Technologies
0.68
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.