Digital Design
Connected Electric Truck Powertrain: Non-Invasive Fault Detection using Ultra-Low Power Edge AI Sensor Network
Audience:
Digital Design Professionals, Electric Vehicle Powertrain Designers, IoT and Big Data Experts
Digital Design Professionals, Electric Vehicle Powertrain Designers, IoT and Big Data Experts
Keyword:
Artificial Intelligence, E-Volve Cluster, Fault Detection Algorithms, Machine Learning, RHODaS, Sensor Technologies
Artificial Intelligence, E-Volve Cluster, Fault Detection Algorithms, Machine Learning, RHODaS, Sensor Technologies
Link:
IEEE Xplore
Electric Vehicle Operations
Data-Driven Approaches to Battery Health Monitoring in Electric Vehicles Using Machine Learning
This article explores battery health monitoring in electric vehicles (EVs) using machine learning to address challenges in battery durability and enable new business models.
Audience:
Electric Vehicle Manufacturers, Electric Vehicle Owners and Consumers, Energy and Utility Companies, Fleet Managers and Operators, Government and Regulatory Bodies, Researchers
Electric Vehicle Manufacturers, Electric Vehicle Owners and Consumers, Energy and Utility Companies, Fleet Managers and Operators, Government and Regulatory Bodies, Researchers
Keyword:
Artificial Intelligence, Battery Health, Computer Science, Data Science, Data-Driven Approaches, Electric Vehicles, Industry 4.0, Internet of Things, Machine Learning, Smart Manufacturing, Vehicle, Vehicle Reliability
Artificial Intelligence, Battery Health, Computer Science, Data Science, Data-Driven Approaches, Electric Vehicles, Industry 4.0, Internet of Things, Machine Learning, Smart Manufacturing, Vehicle, Vehicle Reliability
Link:
researchgate.net