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https://doi.org/10.21278/TOF.501073724

Regenerative Braking Control of Electric Vehicles Using Electro-Mechanical Brakes Based on Improved Whale Optimisation Algorithm

Zhen Lei ; School of Automotive Engineering, Yancheng Institute of Technology, Yancheng, China
Hongming Lyu ; School of Automotive Engineering, Yancheng Institute of Technology, Yancheng, China *

* Dopisni autor.


Puni tekst: engleski pdf 3.559 Kb

str. 85-104

preuzimanja: 135

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Sažetak

To improve the energy utilisation efficiency and driving range of electric vehicles, this paper proposes two strategies: a brake energy recovery control strategy and an electric braking force optimisation algorithm based on electro-mechanical brakes (EMBs). First, a three-stage control system for the EMBs is designed using an active disturbance rejection control (ADRC) algorithm. Next, a brake force distribution strategy that uses a safety zone rule to dynamically adjust the brake force distribution according to real-time operating conditions is proposed based on the ideal brake force distribution curve and the ECE regulation line. This ensures effective braking performance. Then, the whale optimisation algorithm (WOA) is introduced with improvements to its adaptive inertia weight and nonlinear convergence factor to optimise the motor torque control and improve the braking energy recovery efficiency. Finally, co-simulations were performed in MATLAB/Simulink and AVL Cruise for two typical conditions: the worldwide harmonised light vehicle test cycle (WLTC) and China light-duty vehicle test cycle (CLTC). The simulation results show that the three-stage control system designed with the ADRC algorithm outperforms the standard EHB system and that the optimised motor braking force using the improved WOA can recover more energy during braking.

Ključne riječi

electro-mechanical braking system; active disturbance rejection control; improved whale optimisation algorithm; braking energy recovery

Hrčak ID:

345716

URI

https://hrcak.srce.hr/345716

Datum izdavanja:

22.1.2026.

Posjeta: 333 *