4.6 Article

Accurate and Efficient Energy Management System of Fuel Cell/Battery/Supercapacitor/AC and DC Generators Hybrid Electric Vehicles

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SUSTAINABILITY
卷 15, 期 13, 页码 -

出版社

MDPI
DOI: 10.3390/su151310102

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hybrid electric vehicle; energy management strategy; fuel cell; battery; supercapacitor; energy storage; fuel consumption; artificial intelligence; DTC-SVM

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The development of hybrid electric vehicles (HEVs) is gaining momentum as a solution for reducing carbon emissions and improving fuel efficiency. The fuel cell/battery/supercapacitor HEV (FC/Bat/SC HEV) has emerged as a particularly promising choice due to its efficient energy management and adaptability to different driving requirements. This study presents a novel approach for harnessing the kinetic energy of a sensorless HEV, utilizing a combination of fuel cell, supercapacitor, and lithium-ion battery energy storage banks. By exploiting additional DC and AC generators linked to the vehicle's front wheels, the system is able to capture free kinetic energy and achieve high supply efficiency, reducing the reliance on fuel cells and batteries and resulting in significant fuel consumption reduction.
The development of hybrid electric vehicles (HEVs) is rapidly gaining traction as a viable solution for reducing carbon emissions and improving fuel efficiency. One type of HEV that is gaining significant interest is the fuel cell/battery/supercapacitor HEV (FC/Bat/SC HEV), which combines fuel cell, battery, supercapacitor, AC, and DC generators. These FC/B/SC HEVs are particularly appealing because they excel at efficiently managing energy and cater to a wide range of driving requirements. This study presents a novel approach for exploiting the kinetic energy of a sensorless HEV. The vehicle has a primary fuel cell resource, a supercapacitor, and lithium-ion battery energy storage banks, where each source is connected to a special converter. The obtained hybrid system allows the vehicle to enhance autonomy, support the fuel cell during low production moments, and improve transient and steady-state load requirements. The exploitation of kinetic energy is performed by the DC and AC generators that are linked to the electric vehicle front wheels to transfer the HEV's wheel rotation into power, contributing to the overall power balance of the vehicle. The energy management system for electric vehicles determines the FC setpoint power through the classical state machine method. At the same time, a robust speed controller-based artificial intelligence algorithm reduces power losses and enhances the supply efficiency for the vehicle. Furthermore, we evaluate the performance of a robust controller with a speed estimator, specifically using the adaptive neuro-fuzzy inference system (ANFIS) and the model reference adaptive system (MRAS) estimator in conjunction with the direct torque control-support vector machine (DTC-SVM), to enhance the torque and speed performance of HEVs. The results demonstrate the feasibility and reliability of the vehicle while utilizing the additional DC and AC generators to extract free kinetic energy, both of which contributed to 28% and 24% of the total power for the vehicle, respectively. This approach leads to a vehicle supply efficiency exceeding 96%, reducing the burden on fuel cells and batteries and resulting in a significant reduction in fuel consumption, which is estimated to range from 25% to 35%.

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