Liu, Tong (Volvo Group Trucks Technology), Tan, Kaige (KTH Royal Institute of Technology), Zhu, Wenyao (KTH Royal Institute of Technology), Chen, Peigen (Halmstad university), Feng, Lei (KTH Royal Institute of Technology)

An Event-Triggered Control Mechanism to Improve Online Computation Efficiency of Energy Management Strategies for Hybrid Electric Vehicles

Scheduled for presentation during the Regular Session "Electric Vehicles - Charging and Scheduling II" (FrAT3), Friday, September 27, 2024, 10:50−11:10, Salon 6

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), September 24- 27, 2024, Edmonton, Canada

This information is tentative and subject to change. Compiled on October 3, 2024

Abstract

The superiority of hybrid electric vehicles (HEVs) in energy efficiency highly relies on real-time executions of their energy management strategies (EMSs). Most current EMSs merely seek numeric optimality but neglect computation efficiencies in real-time applications. Hence, these EMSs usually suffer from tremendous computation overheads in practice and thus cannot be executed by onboard embedded processors. Consequently, this paper introduces an event-triggered control mechanism to replace the periodic torque split controller. When the HEV is in hybrid mode, an efficient trigger algorithm at each step determines whether the torque split controller needs to calculate a new solution or the previous solution is still valid. In this way, a large percentage of unnecessary computation overheads is avoided when the powertrain torque demand is unchanged. The advantages of this event-triggered control mechanism are demonstrated by processor-in-the-loop (PIL) simulations on different testing cycles. In contrast to the EMS with a fixed period, the event-triggered controller can significantly reduce both maximum and average CPU utilization in online testing without obviously compromising energy efficiency.