PhD Transitioning Fleets to Net Zero Using a Predictive Model of Powertrain Performance in Loughborough United Kingdom | Loughborough University

Reaching Net Zero requires fleet operators like emergency services (including Police Forces) to evaluate the intricate relationship between various vehicle types, their performance needs, and unconventional driving patterns. In these scenarios, standard metrics for efficiency and range often don't apply, making the shift to zero-emission vehicles more challenging.

Our initiative focuses on assessing fleet vehicle needs to determine the best electric vehicle options for specific roles. This approach creates a roadmap for achieving net zero emissions while meeting service delivery goals.

By examining individual driving patterns and their effects on battery performance and lifespan, the study aims to create an innovative predictive algorithm for powertrain usage across diverse conditions—including varied landscapes, weather, and driving techniques. Considering operational factors like shift schedules, unpredictability, charging logistics, infrastructure costs, procurement, and lifecycle aspects enables comprehensive, data-driven decisions for fleet transition and future operational planning.