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A New Approach to the Test, Assessment and Optimization of Robust Electrical Distribution Systems

Journal Article
2013-01-0396
ISSN: 1946-3979, e-ISSN: 1946-3987
Published April 08, 2013 by SAE International in United States
A New Approach to the Test, Assessment and Optimization of Robust Electrical Distribution Systems
Sector:
Citation: Brabetz, L., Ayeb, M., Jilwan, G., Graebel, P. et al., "A New Approach to the Test, Assessment and Optimization of Robust Electrical Distribution Systems," SAE Int. J. Mater. Manf. 6(3):382-388, 2013, https://doi.org/10.4271/2013-01-0396.
Language: English

Abstract:

Both the electrical portion of the powertrain and the rising number of auxiliary systems will considerably increase the electrical power requirements in future vehicles. In addition, multiple voltage supply levels will enhance the complexity of the electrical distribution system (EDS), while strict cost, weight, packaging, and safety constraints must be upheld, posing serious design challenges in terms of robustness, reliability and energy efficiency.
Currently, a self-contained integral test or evaluation of the EDS is normally not applied. For such a purpose, quantitative quality criteria are introduced here which allow a comparative assessment of an EDS by addressing the dynamic and static stability of the supply voltage, the reliability of the fusing system, and the ability to provide the required electrical power.
The presented approach uses both precisely-defined test scenarios and a comprehensive EDS test bench. It is based on a hardware-in-the-loop (HiL) system with an extensive measurement set-up allowing the determination of the quality criteria mentioned above. Thus, thorough investigations into the impact of the dimensioning of EDS components as well as of new architectures can be conducted. In addition, a quantitative performance benchmarking and the identification of functional risks or of potentials for optimization are possible. The paper presents the theoretical description and initial experimental data, followed by a discussion of the next steps, for instance the application of the method to simulation, as well as a look at future possibilities.