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Implementation of an Automation System to Support Test Case Execution and Classification for Electrical Tests

In recent years, automotive engineering becomes more challenging and complex than previous years because of the innovation that transformed the cars powertrain system. By the quick developing of the automotive systems and increasing the consumer demand for Hybrid Vehicles (HV), Electric Vehicles (EV) and Autonomous cars, authenticity and security of engine systems
are an essential part. The Hybrid Electric Vehicle structure contained several system sections like Electric Motor, Inverter, DC-DC Converter, etc. For testing this device, OEM’s are providing a special automotive standard norm (these norms are individually defining by automotive companies as LV124/123/148) which used for simulates variety of the electrical disturbances and monitoring the system behavior. This standard profile applies, simulates and
records by EM Autowave system. Electrical tests have been done for a long time manually. Manual testing takes a huge amount of time, money and human resources. Based on the facts, the thesis purpose is to provide the
automated system test for supporting test case execution on the HEV test bench, and offline classification independent of the test bench. This scope of the project will be developed by adapting automation library which is going to equip new features for automation system tool.
On the other hand, in order to conform the test simulator and their communication system, a device file is implemented for loading and testing the electrical profiles on the test bench system. In addition, automated classification and evaluation used Matlab functions and the test result will be provided as plots which makes differential discovering very easier.

Identiferoai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:36119
Date14 November 2019
CreatorsBabakhani, Mohammad Reza
ContributorsHardt, Wolfram, Theologidis, Margaritis, Technische Universität Chemnitz
Source SetsHochschulschriftenserver (HSSS) der SLUB Dresden
LanguageEnglish
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/publishedVersion, doc-type:masterThesis, info:eu-repo/semantics/masterThesis, doc-type:Text
Rightsinfo:eu-repo/semantics/openAccess

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