Optimized barrier-condition nonlinear control of wireless charger-based hybrid electric vehicle

BT Gul, SH Ahmed, I Ahmad, O Zeb - Journal of Energy Storage, 2024 - Elsevier
BT Gul, SH Ahmed, I Ahmad, O Zeb
Journal of Energy Storage, 2024Elsevier
Plug-in hybrid electric vehicles can be replaced by wireless charger-based electric vehicles
because wireless power transfer is easier, safer, and more suitable for usage, especially in
moist environmental conditions. In this paper, the wireless charger-based electric vehicle
comprises two subsystems: an inductor-capacitor-capacitor series compensation network-
based wireless charging system and a hybrid energy storage unit. The hybrid energy
storage unit comprises a regenerative fuel cell that combines an electrolyzer with a fuel cell …
Abstract
Plug-in hybrid electric vehicles can be replaced by wireless charger-based electric vehicles because wireless power transfer is easier, safer, and more suitable for usage, especially in moist environmental conditions. In this paper, the wireless charger-based electric vehicle comprises two subsystems: an inductor-capacitor-capacitor series compensation network-based wireless charging system and a hybrid energy storage unit. The hybrid energy storage unit comprises a regenerative fuel cell that combines an electrolyzer with a fuel cell, a battery, and a supercapacitor. The primary function of the electrolyzer is to generate hydrogen to be utilized by the fuel cell. The wind-up effect manifests when integral error accumulates leading to overshoots and oscillations. The conventional super twisting-based sliding mode controller (ST-SMC) exhibits a wind-up phenomenon due to integral error accumulation and it can only cater to disturbances with known bounds. To address this issue, a barrier-condition-based super twisting sliding mode controller has been proposed to reduce the wind-up phenomenon when the integral error accumulates and cater to the disturbances with unknown bounds. Furthermore, an energy management system has been proposed to maintain a power balance between the state of charge of the supercapacitor and the battery as inputs. Lyapunov stability analysis has been used to ensure the asymptotic stability of the system. Controller gains have been tuned using the grey wolf optimization technique. Other controllers like ST-SMC and sliding mode control have also been proposed for performance comparison. Finally, the overall performance of the proposed controller has been validated using MATLAB/Simulink as well as through a Delfino-based real-time hardware-in-the-loop (HIL) setup.
Elsevier
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