Approach to Assimilate External Weather Information to Onboard Vehicle Measurements to Account for Weather-Related Impact Factors

Weather conditions along a route have enormous influence on the energy demand of battery electric vehicles. However, it is difficult to determine current and especially future weather conditions, in particular the temperature profile along a route. On the one hand each vehicle has its own measurement tolerances, and the temperature measurement can be disturbed. On the other hand, local weather stations cannot accurately reflect local conditions. In this work, we match weather information from various external weather databases with real on-board vehicle weather measurements to better apply weather forecasts from external providers to the vehicle. The objective is to ensure that predicted weather information along a future route is processed using multiple linear regression (MLR) and made available to the system as the vehicle would experience them passing by. Taking vehicle measurements as ground truth for the MLR, energy prediction models can consider weather information as inputs to in vehicle models along a route. We refer separately to two methods of weather forecast utilization. The implementation and evaluation are based on real driving data in the context of temperature prediction along a route. ... mehrWe highlight factors that can improve the assimilation of weather data to a vehicle.