Electric Vehicle Charging Service Operations: a Review of Machine Learning Applications for Infrastructure Planning, Control, Pricing and Routing

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Özet

The majority of global road transportation emissions come from passenger and freight vehicles. Electric vehicles (EV) provide a sustainable transportation way, but customers’ charging service related concerns affect the EV adoption rate. Effective infrastructure planning, charge scheduling, charge pricing, and electric vehicle routing strategies can help relieve customer perceived risks. The number of studies using machine learning algorithms to solve these problems is increasing daily. Forecasting, clustering, and reinforcement based models are frequently the main solution methods or provide valuable inputs to other solution procedures. This study reviews the studies that apply machine learning models to improve EV charging service operations and provides future research directions. © 2023 Elsevier Ltd

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Anahtar kelimeler

Charge scheduling, Charging service operations, Electric vehicle, Infrastructure planning, Machine learning, Pricing, Routing, Charging (batteries), Electric vehicles, Learning algorithms, Reinforcement learning, Vehicle routing, Charge scheduling, Charging service operation, Electric vehicle charging, Infrastructure planning, Machine learning applications, Machine-learning, Planning controls, Road transportation, Routings, Service operations, Costs, Infrastructure planning, Electric vehicles, Machine learning applications, Charge scheduling, Electric vehicle, Learning algorithms, Service operations, Machine learning, Reinforcement learning, Machine-learning, Routing, Road transportation, Electric vehicle charging, Planning controls, Vehicle routing, Costs, Charging (batteries), Routings, Charging service operation, Charging service operations, Pricing

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0211 other engineering and technologies, 02 engineering and technology, 0202 electrical engineering, electronic engineering, information engineering

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58

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Renewable and Sustainable Energy Reviews

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188

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113873

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