Validation of automotive centrals using hardware in the loop -BCM and Lights
1 Product Engineering Stellantins South America - Federal University of Minas Gerais, Brazil.
2 Department of Electrical Engineering - Federal University of Minas Gerais, Brazil.
Review Article
Global Journal of Engineering and Technology Advances, 2023, 14(03), 188–204.
Article DOI: 10.30574/gjeta.2023.14.3.0027
Publication history:
Received on 05 January 2023; revised on 26 March 2023; accepted on 29 March 2023
Abstract:
The race for electrification and the need for innovation to attract customers has driven the automotive industry to do something different in vehicles, emerging emission control challenges and efficient technological availability are the pillars of innovation. With the need to upgrade industrial manufacturing systems, directly impacting vehicle production, established the search for new prototyping methodologies and use of virtual tools for testing, validation of components and vehicle systems are developed. The demand for electronic components controls units (ECU) is growing, due to the availability of intelligence and security in today's vehicles, directly impacting their development and the performance and functionality tests. To meet this new reality, in addition to the automotive test prototypes used during development, the automotive industry has been using different virtual environments to produce, verify, and validate its vehicles. Therefore, this paper applied integration and validation using the HIL test platform, focusing on the ECU Body Control Unit (BCM), analyzing its functionalities and possible failures of the internal and external light loads. After, a brief commentary will be made exposing other test medium platforms given as the Plywood Buck (PWB), checking the reliability, flexibility, installation time, and costs of the three test platforms Software in the loop (SIL), Model in the loop (MIL) , Hardware in the loop (HIL), in order to verify their advantages, challenges, and problems in the use and information to optimize the use of each platform and test medium.
Keywords:
Automotive; Validation; xIL; Optimization
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Copyright © 2023 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0