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Published June 30, 2020 | Version v1
Journal article Open

Software Product Validation of Body Controller ECU's using Intelligent Automation Methods

  • 1. assistant professor, Electronics and Communication Engineering, Jss Science and technological University, Mysuru, Karnataka, PIN-570008, India.
  • 2. MTech, Automotive Electronics, Jss Science and technological University, Mysuru, Karnataka, PIN-570008, India.
  • 3. Senior manager, Continental automotive component private limited, Bangalore, India.
  • 1. Publisher

Description

In Continental the, Electronic Control Unit (ECU’s) software consists of 2 parts, the basic software which is the generic part and the application software which does the product specific functionality. The project specific functionality depends upon the product type, like Body domain controller, immobilizer etc. Before the ECU is going to mass production, the controller has to be validated i.e., software and hardware. The main reason is to ensure, that once the ECU is fitted to the vehicle and there is a recall for ECU, it involves additional cost to the organization. The validation of the software includes, checking of the micro controller input, outputs, peripheral drivers, the initialization of the drivers, the timing measurement of the different components. All the parameters are controlled by the generic and application specific modules, and can be configured via configuration tool, manual configuration etc. Since the SW modules are complex and huge, so its need to perform validation of the SW modules manually. This is time consuming process, as it involves checking many c file, configuration files etc. The proposal is to automate the process using Python programming, which interacts with the C code, configuration files, debugger, interacting with the ECU’s peripherals, components and validate the Software parameters before going for series production. In the proposed method the different steps can be automated for different micro-controllers i.e., Renesas RL78 and RH850 used in the ECU’s and different architecture i.e., AUTOSAR and NON-AUTOSAR will be considered and the results will be compared with the manual validation effort and accuracy.

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Journal article: 2249-8958 (ISSN)

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ISSN
2249-8958
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E9831069520/2020©BEIESP