Ford Explores More Accurate Method for Predicting Electric Vehicle Range
Back in 2011, Ford’s Research and Advanced Engineering team began exploring ways in which it could more accurately estimate electric vehicle energy consumption.
Ford believed that if energy consumption could be fully understood, then range predictions would be far more precise. It was from this that Ford set out to explore how traffic simulators and vehicle propulsion impacted energy consumption and range.
Ford’s resulting work is now found in the book titled “Simulation and Modeling Methodologies, Technologies and Applications.”
A snippet of the work from that book, courtesy of Green Car Congress, is found below:
“To alleviate range anxiety, new vehicle electronics features are needed to help vehicle operators make diving choices that avoid discharged battery situations, extend vehicle range, and combine charging with other good uses of time. Development of these features requires practical meta-models that can accurately predict energy consumption on public roads.”
“Building meta-models from field-test data requires statistical regression of public-road vehicle data (PRVD) over very large geographic areas. At present there are not enough production test vehicles available to collect a sufficient amount of data, noise factors are not well controlled, and data collection is too time consuming to support product launch. As a results modeling and simulation are essential tools in analysis of BEV performance.”
“In this work we propose implementation of traffic simulation combined with propulsion modeling for determining electric vehicle energy consumption. We use traffic micro-simulation to create surrogate PRVD data that has many of the properties of actual PRVD data, specifically capturing the stochastic nature of vehicles moving through roads with traffic. The surrogate data is analyzed using propulsion simulation to estimate the amount of energy the vehicles will consume in a specific driving maneuver to derive statistical information.”
We’re sure that the rest of the book is written in this overly technical manner and that it would be a bore to read, but what’s important here is that automakers understand that range predictions must be accurate and that they’re working on a solution that’s as precise as possible.