Affiliation:
1. School of Mechanical and Electrical Engineering, Guilin University of Electronic Technology, Guilin 541004, China
2. School of Mechanical and Automotive Engineering, Guangxi University of Science and Technology, Liuzhou 545616, China
3. Commercial Vehicle Technology Center, Dong Feng Liuzhou Automobile Co., Ltd., Liuzhou 545005, China
Abstract
Road slope is an essential parameter in the study of vehicle driving processes. In future traffic development, constructing road segments with slopes is indispensable. Furthermore, road slope is a fundamental parameter for realizing energy recovery during braking. Hence, research on road slope estimation is extremely crucial. This article proposes a combination of adaptive filtering and strong tracking filter factors for road slope estimation, followed by establishing case settings for verification. It was found that the proposed slope estimation algorithm has a high degree of accuracy in estimating the slope angle, with a mean absolute error (MAE) and a root mean square error (RMSE) of 0.0254 and 0.0359, respectively, at fixed slopes, and a MAE and a RMSE of 0.2799 and 0.3710, respectively, at varying slopes. By combining the slope angle with a braking force distribution optimization algorithm, an optimized braking distribution coefficient is obtained. In the Cruise2019 software, slope angles of 0° and 5° are set and combined with the braking force distribution strategy built in Matlab2021/Simulink for verification under China Heavy-duty Commercial Vehicle Test Cycle (CHTC-HT) and Worldwide Transient Vehicle Cycle (C-WTVC) conditions. The recovered energy increased by 7.24% and 4.99%, respectively, under CHTC-HT conditions, and by 6.42% and 1.73%, respectively, under C-WTVC.
Funder
Innovation-Driven Development Special Fund Project of Guangxi
central government guides local funds for scientific and technological development
Science and Technology Planning Project of Liuzhou
Liudong Science and Technology Project
Reference29 articles.
1. Model Predictive Control of Regenerative Braking for Hybrid Electric Vehicle Cruising Downhill;Shu;J. Highw. Transp. Res. Dev.,2011
2. Downhill safety assistance control for hybrid electric vehicles based on the downhill driver’s intention model;Luo;Proc. Inst. Mech. Eng. Part D J. Automob. Eng.,2015
3. The fuel cell electric vehicle market growth: Analyses of contracts and government incentives;Comput. Ind. Eng.,2023
4. Shah, P. (2019). Fuel Cell Vehicle Market Research Report Analysis and Growth Forecast to 2024 Market Overview, LinkedIn Corporation.
5. Development and future prospect of the hydrogen fuel cell vehicle at home and abroad;Xin;Automob. Appl. Technol.,2019