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Implementation of Dual-Circuit System for Additional Power Supply Based on Photovoltaic Converters for Electric Vehicles
摘要： The article presents a process of designing the photovoltaic (PHV) converters system for an electric vehicle, shows the scheme of photovoltaic converters usage, the results of electric vehicle motion modeling with photovoltaic converters, and the results of road tests of an electric vehicle with an additional power source based on photovoltaic converters. The photovoltaic converters system and low-voltage system of an electric vehicle have a shared low-voltage battery, which allows the implementation of two schemes of electric vehicle power supply. Initially, the aggregate base was selected, then, taking into account the e?ciency of each device included in the design of the new electric vehicle, mathematical modeling was carried out and showed good e?ciency results of the photovoltaic converters system. Then, the prototype was manufactured and tested. The aggregate base included the battery of photovoltaic converters assembled in a certain way on the vehicle roof, the MPPT (maximum power point tracking) controller, the bu?er storage device in the form of a 12 V battery, and the DC (direct current) converter that allows transmitting electricity from the bu?er battery to the high-voltage system. Modeling of the electric vehicle motion considered typical operating modes, including energy costs for the operation of assistant systems of the electric vehicle, as well as including the consumption of low-voltage components. The tests were carried out according to the NEDC (New European Driving Cycle). As a result, implementation of photovoltaic converters with 21% e?ciency allowed for the power reserve of the electric vehicle to be increased by up to 9%.
关键词： charging system,photovoltaic converter,electric vehicles,hybrid,photoelectric converters,solar battery,electric vehicle,charging infrastructure
更新于2025-09-23 15:19:57
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Optimal Hybrid Neuro-fuzzy Based Controller Using MOGA for Photovoltaic (PV) Battery Charging System
摘要： This paper proposes an optimal hybrid neuro-fuzzy/fuzzy controller based on maximum power point tracking (MPPT) technique and voltage regulation for photovoltaic lead-acid battery charging system through the constant current and constant voltage (CC-CV) charge, denoted by NFC-CC/FLC-CV. The parameter optimization of NFC and FLC, including rule selection, based on multi-objective genetic algorithm (MOGA) is applied to the NFC-CC design to improve the tracking accuracy while reducing complexity. By means of genetic optimization, the number of fuzzy rules can be greatly reduced by 50%. In addition, GA is applied to the FLC-CV design to increase voltage regulation (VR) accuracy. After satisfying the stability condition through the solutions determined by MOGA and GA, the performances of controllers under rapidly-changing weather are evaluated tradeoff by several creteria, including transient response, stabilized accuracy, charging time, and energy utilization and charging ef?ciency. As results, the proposed controller outperforms the other existing controllers with the fastest rise time without overshoot, the highest MPPT and VR accuracy with negligible oscillations, a 12-23% reduction in charging time, and an increase of 5-15% and 1-6% in energy utilization and charging ef?ciency. Furthermore, it provides superior results in terms of computational complexity by achieving the minimum number of multiplications and system parameters, and high reliability with the lowest Akaike information criterion (AIC).
关键词： MPPT,neuro-fuzzy,Fuzzy logic,MOGA,photovoltaic charging system
更新于2025-09-10 09:29:36