Next Article in Journal
In-Situ Plasticized LLZTO-PVDF Composite Electrolytes for High-Performance Solid-State Lithium Metal Batteries
Next Article in Special Issue
Model Predictive Control for Residential Battery Storage System: Profitability Analysis
Previous Article in Journal
In Situ Solidification by γ−ray Irradiation Process for Integrated Solid−State Lithium Battery
Previous Article in Special Issue
Fractional-Order Sliding-Mode Observers for the Estimation of State-of-Charge and State-of-Health of Lithium Batteries
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Battery Test Profile Generation Framework for Electric Vehicles

1
State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
2
Beijing Circue Energy Technology Co., Ltd., Beijing 100085, China
*
Author to whom correspondence should be addressed.
Batteries 2023, 9(5), 256; https://doi.org/10.3390/batteries9050256
Submission received: 26 March 2023 / Revised: 25 April 2023 / Accepted: 27 April 2023 / Published: 29 April 2023
(This article belongs to the Special Issue Battery Energy Storage in Advanced Power Systems)

Abstract

This paper proposes a framework for generating a battery test profile that accounts for the complex operating conditions of electric vehicles, which is essential for ensuring the durability and safety of the battery system used in these vehicles. Additionally, such a test profile could potentially accelerate the development of electric vehicles. To achieve this objective, the study utilizes a simplified longitudinal dynamics model that incorporates various factors such as the drivetrain efficiency, battery system energy conversion efficiency, and regenerative braking efficiency. The battery test profile is based on the China light-duty vehicle test cycle-passenger car (CLTC-P) and is validated through testing on an electric vehicle with a chassis dynamometer. The results indicate a high degree of consistency between the generated and measured profiles, confirming the efficacy of the simplified longitudinal dynamics model.
Keywords: simplified longitudinal dynamics model; electric vehicles; battery test profile; sensitivity analysis simplified longitudinal dynamics model; electric vehicles; battery test profile; sensitivity analysis

Share and Cite

MDPI and ACS Style

Guo, D.; Ren, H.; Feng, X.; Han, X.; Lu, L.; Ouyang, M. Battery Test Profile Generation Framework for Electric Vehicles. Batteries 2023, 9, 256. https://doi.org/10.3390/batteries9050256

AMA Style

Guo D, Ren H, Feng X, Han X, Lu L, Ouyang M. Battery Test Profile Generation Framework for Electric Vehicles. Batteries. 2023; 9(5):256. https://doi.org/10.3390/batteries9050256

Chicago/Turabian Style

Guo, Dongxu, Hailong Ren, Xuning Feng, Xuebing Han, Languang Lu, and Minggao Ouyang. 2023. "Battery Test Profile Generation Framework for Electric Vehicles" Batteries 9, no. 5: 256. https://doi.org/10.3390/batteries9050256

APA Style

Guo, D., Ren, H., Feng, X., Han, X., Lu, L., & Ouyang, M. (2023). Battery Test Profile Generation Framework for Electric Vehicles. Batteries, 9(5), 256. https://doi.org/10.3390/batteries9050256

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop