Hirata, Mitsuo (Utsunomiya University), Mori, Daiki (Utsunomiya University)

Fuel-Efficient Control Via Accelerator Mitigation in Series HEVs Using Nonlinear MPC

Scheduled for presentation during the Regular Session "Vehicle energy management" (MoA3), Monday, June 16, 2025, 11:40−12:00, August

AAC 2025 11th IFAC International Symposium on Advances in Automotive Control, June 15-18, 2025, Eindhoven, Netherlands

This information is tentative and subject to change. Compiled on May 31, 2025

Abstract

The energy management of hybrid electric vehicles (HEVs) is significantly influenced by driver behavior, often leading to reduced fuel efficiency. This study proposes a model predictive control (MPC)-based system to improve fuel efficiency by modifying the driver's accelerator input. A neural network state-space model is employed to capture the complex dynamics of HEVs. Simulations using an HEV simulator validate the effectiveness of the proposed method in enhancing fuel efficiency. These results demonstrate the potential of combining MPC with neural network modeling to overcome the challenges posed by driver behavior in HEV energy management.