Pritpal Singh
Bio
Dr. Pritpal Singh is a Professor of Electrical Engineering at Villanova University. He received his BSc in Physics from the University of Birmingham in England in 1978 and his Ph.D. in Applied Science/Electrical Engineering from the University of Delaware in 1984.
Dr. Singh has been a Professor of Electrical Engineering at Villanova University for 40 years. He teaches post-graduate courses in power electronics, renewable energy systems, electrochemical power sources, and smart grid systems and undergraduate courses in analog electronics. He has over 25 years of research experience in energy storage and performed pioneering work in fuzzy logic-based state-of-charge (SoC) and state-of-health (SoH) estimation of batteries for a wide variety of chemistries and PEM fuel cells. He has designed and built battery management instrumentation. He has over 150 peer reviewed conference and journal publications and has consulted for the US Department of Energy on thin film solar cell research as well as energy systems. His recent research has been focused on design and analysis of microgrids, especially in remote communities. Dr. Singh was awarded the International Federation of Engineering Education Societies (IFEES) 2022 Duncan Fraser Award for Excellence in Engineering Education.
The precise measurement of DC Internal Resistance (DCIR) of a Sealed Lead-Acid Battery (SLAB) is of significant importance to accurately estimate the battery’s State-of-Health (SoH), which indicates its performance and cycle age. However, a seemingly simple DCIR measurement has been a challenge, since its value changes continuously – during the battery’s charge, discharge, idle period, and even during its measurement duration. This research developed a simple and practical method, which is accurate, repeatable, and can measure the DCIR of 12 V, 200 Ah SLABs, for a given charge level and at the specified load current. DCIR values comprise the ohmic resistance and the resistance due to electrochemical processes. Some available measurement methods were first evaluated. These methods included fixed DC load, two-tier DC load, and the voltage relaxation technique. The limitations of these methods pertain to poor repeatability, subjectivity, and inconsistency of results. Next, we present our successful experiments to identify two Virtual Open Circuit Voltage (VOCV) based novel methods. The selected new method is one of these two methods, based on the pre-validated concept of VOCV. We notably present the results of the DCIR variations with the battery’s SoC, for ninedistinct life stages during the battery’s cycle life. The results showed an increase in DCIR, with a reduction in SoC and cycle age. This increase is significant at the End-of-Discharge Voltage (EODV) levels. The DCIR decrease with an increase in load current was demonstrated. The experimental results will facilitate future work to generate a valuable battery database that provides – cycle age, SoC, SoH, and battery calendar life and cycle life studies. DCIR and battery impedance may provide more accurate battery reactive components.
