As part of the Horizon Europe-funded NextETRUCK project, researchers from consortium partners CIDETEC Energy Storage and TECNALIA have published new findings that could significantly enhance the efficiency and safety of electric vehicle battery systems. The peer-reviewed article, “Model Predictive Control as the Cloud Control Strategy for a Battery Thermal Management System”, presents a novel cloud-based approach to managing battery temperatures through predictive control.

The research addresses a critical technical challenge in electric mobility: maintaining optimal battery temperatures during high-demand scenarios, such as fast charging. Using a model predictive control (MPC) strategy hosted in the cloud, the authors propose a control architecture that dynamically optimises the operation of the battery thermal management system (BTMS). This approach enables real-time thermal regulation, prolongs battery lifespan, and reduces overall energy consumption.

What sets this work apart is its integration of advanced digital models representing the battery system, battery management system (BMS), electronic control unit (ECU), and thermal control subsystems. These models allow for extensive simulations of operational conditions and deliver evidence on the advantages of predictive control. The study demonstrates how MPC can effectively balance energy savings—achieving a 1% reduction in energy consumption during complete drive cycles—with improved thermal safety across all battery components.

Read the full article on the NextETRUCK website here

Read the paper here