APPLICATION OF SOFTWARES AND DIGITAL PLATFORMS FOR PRECISE AUTOMOTIVE DIAGNOSIS; LEVERAGING MANUFACTURER DATA ANALYSIS.

Authors

  • Fabián Eduardo Vilema Chuiza Instituto Superior Universitario Carlos Cisneros
  • Silvia Valeria Castelo Quinde Instituto Superior Universitario Carlos Cisneros

DOI:

https://doi.org/10.59540/tech.vi4.74

Keywords:

BMS, KIA, software, platform, BAS, MHEV

Abstract

The evolution of the automotive industry brings with it the increase of electronic systems in the car, allowing the diagnostic process to be more complex and take a drastic change seeing the need to apply computational tools that allow to reduce the stages in the electronic diagnosis. The main objective of this study is to analyze the efficiency of the automotive diagnosis by applying digital platforms of the manufacturer in particular, the same ones that allow to direct the analysis of the DTC that are located during the experimentation stage of the vehicle under study, considering that the automotive diagnostic platforms of the manufacturer offer analysis of electrical diagrams, repair manuals, reprogramming processes for the ECUs in addition to identifying the breakdown processes where exact data is appreciated that allow to know each one of the processes established for the cases where the electronics of the car present defects resulting in the out-of-range operation of the affected system. For the case study, fault codes are extracted from a KIA brand MHEV vehicle, STONIC model from 2024, which presents faults in the charging of the low voltage battery, being necessary to apply the processes established by the manufacturer in its digital platform. The scientific method applied is of the quantitative type with a non-experimental approach considering that information samples will be taken from the electronic control unit of the vehicle's high voltage battery that can deliver under fault states and ideal operation.

 

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Published

2025-01-06

How to Cite

[1]
F. E. Vilema Chuiza and S. V. Castelo Quinde, “ LEVERAGING MANUFACTURER DATA ANALYSIS”., TECH, no. 04, p. 11, Jan. 2025.