Improvement of Industrial Applications with AI-Powered Power Quality Monitoring in Electric Vehicles: Maximizing Smart Energy Management and Predictive Analytics

A revolution is underway in the field of electric vehicle (EV) power quality monitoring thanks to advancements in artificial intelligence (AI), which holds great promise for the enhancement of industrial applications. This research delves into the potential of AI to enhance electric car systems' energy management and predictive analytics. Power quality measures, which are critical for electric vehicle performance, may be effectively monitored and evaluated by artificial intelligence. These metrics include frequency fluctuations, harmonic distortion, and voltage stability. Using algorithms for machine learning and analyzing data in real-time makes this possible. In order to create predictive models that can foresee potential power quality issues, this study's results have prompted research into several AI techniques, including support vector machines and neural networks. As a result, operational downtime will be reduced and preventative maintenance can be carried out. Also, power quality monitoring systems are able to collect and analyze data more efficiently with the help of artificial intelligence (AI) and Internet of Things (IoT) devices. The goal of this research is to highlight the benefits of electric vehicle (EV) power quality monitoring powered by artificial intelligence (AI), such as enhanced user experience, longer battery life, and greater energy efficiency. Electric vehicles in industrial settings may become more dependable and environmentally friendly if artificial intelligence is used to improve power quality control. This could lead to smarter energy management solutions.