Study on the Integration Strategy of Online EOL Testing of Pure Electric Vehicle Power Battery.

EOL testing UDS detection system human–machine interface power battery

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
26 Jun 2023
Historique:
received: 05 05 2023
revised: 17 06 2023
accepted: 25 06 2023
medline: 17 7 2023
pubmed: 14 7 2023
entrez: 14 7 2023
Statut: epublish

Résumé

This paper analyzes the electrical test items of the EOL testing line in automotive manufacturers. On this basis, this paper proposes and designs an integrated and automated testing strategy to deal with the problems of slow testing speed, high dependence on manual labor and low efficiency. This article mainly analyzes the various tests of the two main tests in battery EOL testing: Battery Management System (BMS) testing and electrical testing. We propose an innovative integrated solution based on various testing items, including the reception, transmission, and self-analysis of different UDS protocol messages, a unique automated electrical performance measurement scheme, and a requirement and logic design of an integrated software end based on Python. The experimental results of actual testing show that the implementation of the integrated strategy greatly reduces the complexity of the testing steps, improves the testing efficiency, and reduces errors caused by human operation.

Identifiants

pubmed: 37447793
pii: s23135944
doi: 10.3390/s23135944
pmc: PMC10346435
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : National Natural Science Foundation of China
ID : Grant No.72174172, 71774134
Organisme : "the Fundamental Research Funds for the Central Universities",Southwest Minzu University
ID : (Grant No.2021101)

Auteurs

Huazhang Wang (H)

School of Electrical Engineering, Southwest University for Nationalities, Chengdu 610041, China.

Hang Qin (H)

School of Electrical Engineering, Southwest University for Nationalities, Chengdu 610041, China.

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Classifications MeSH