Smart EV Motor Predictive Maintenance System Using IoT

Electric motors sit at the heart of an electric vehicle (EV); in fact, what's more, breakdowns, safety risksand costly repairs are being caused by a sudden motor failure, on the whole. Well the same, after a faulthas already start; motor condition is still mostly verified at fixed service intervals. Low-cost sensors,microcontrollers with built-in Wi-Fi and cloud dashboards now make continuous condition monitoringpractical; this review is evaluating motor fault mechanisms, condition-monitoring methods, sensorbasedmeasurement of temperature, vibration, current and speed, Internet of Things (IoT) architectures,predictive maintenance and health-index methods, and examines recurring obstacles, like noisy signals,false alarms, scarce fault data, changing load conditions and the restricted computing power ofembedded nodes, broadly speaking. The survey is, for all practical purposes, suggesting that mostpublished work tackles one fault indicator at a time or rests on costly instrumentation. When you wantto finish this gap, a Smart EV Motor Predictive Maintenance System is put forward that combinestemperature, vibration, current and speed sensing on an ESP32 microcontroller, finds a motor healthscore, raises early maintenance warnings and offers all data on a real-time IoT dashboard; this model isat the design stage, such as no measured results are reported. Try this instead, we state the targets, theplanned methodology, an evaluation protocol and the outcomes we expect, clearly marked aspredictions to be tested, and argue that such a low-cost platform can shift motor maintenance fromreactive repair to proactive, transparent and doable decisions.