The objective of this research is to develop a combination of physics-, model-, and data-based diagnostic and prognostic algorithms for clawpole synchronous alternators that are widely used in automotive applications. The approach is to meet this objective using only voltage and current sensors. This is accomplished by creating detailed electromagnetic and mechanical models of alternators. Next, diagnostic rules are developed by relating the features of the output current to failure modes. Then, prognostic techniques are developed to predict RUL and fault severity based on test bench data, heuristic progression models, and a comparison to developed models for faulty machines.
Intellectual Merit
The intellectual merit of this research includes an improved understanding of alternator failure mechanisms, and their manifestation in features of the output current, new algorithms for sensorless data-based diagnostics, and new techniques for prognostics which involve the inclusion of heuristic, model-based and experimentally-derived information. These concepts will be proven on actual hardware test platforms and using design data from the manufacturer.
Broader Impacts
Research benefits include the timely and accurate detection of alternator problems which will decrease stranded motorist incidences and significantly decrease misdiagnoses, thereby resulting in warranty cost savings. Also, the project results will improved automotive reliability affects the entire economy, and reduce maintenance costs and warranty costs which directly affect consumer prices. This represents many millions of dollars per year. This technology applied in US cars will improve our countrys competitiveness. Finally, the work on prognostics will benefit all types and applications of electric machines. The research will also contribute to new graduate course content as well as to training of undergraduate and graduate students. Building on existing collaboration with the institution's Opportunity Scholars Program, an effort will be made to recruit students from underrepresented groups.
