Unified Net Willans Line Model for Estimating the Energy Consumption of Battery Electric Vehicles

Author:

Li Candy Yuan1,Nelson Douglas1

Affiliation:

1. Virginia Tech

Abstract

<div class="section abstract"><div class="htmlview paragraph">Due to increased urgency regarding environmental concerns within the transportation industry, sustainable solutions for combating climate change are in high demand. One solution is a widespread transition from internal combustion engine vehicles (ICEVs) to battery electric vehicles (BEVs). To facilitate this transition, reliable energy consumption modeling is desired for providing quick, high-level estimations for a BEV without requiring extensive vehicle and computational resources. Therefore, the goal of this paper is to create a simple, yet reliable vehicle model, that can estimate the energy consumption of most electric vehicles on the market by using parameter normalization techniques. These vehicle parameters include the vehicle test weight and performance to obtain a unified net Willans line to describe the input/output power using a linear relationship. A base model and three normalized models are developed by fitting the UDDS and HWFET energy consumption test data published by the EPA for all BEVs in the U.S. market. Out of the models analyzed, normalizing by weight performs best with the lowest RMSE values at 0.384 kW, 0.747 kW, and 0.988 kW for predicting the UDDS, HWY, and US06 data points, respectively, and 0.653 kW using the combined data of all three data sets. Consideration of accessory loads at 0.5 kW improves the model normalized by weight and performance by a reduction of over 20% in RMSE for predictions with all data sets combined. Removing outliers in addition to the consideration of accessory loads improves the model normalized by weight and performance by a reduction of over 36% in RMSE for predictions with all data sets combined. Overall, results suggest that a unified net Willans line is largely achievable with accessible energy consumption data on U.S. regulatory cycles.</div></div>

Publisher

SAE International

Subject

Artificial Intelligence,Mechanical Engineering,Fuel Technology,Automotive Engineering

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Unified Net Willans Line Model for Estimating the Energy Consumption of Battery Electric Vehicles;SAE International Journal of Advances and Current Practices in Mobility;2023-04-11

2. Energy Modeling of Deceleration Strategies for Electric Vehicles;SAE Technical Paper Series;2023-04-11

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