Prognostics and Health monitoring of Lead acid battery

##plugins.themes.academic_pro.article.main##

Ashwin R
Dr.Suryanarayana Prasad A.N

Abstract

The ever-increasing number of electrical loads in the commercial vehicle emphasizes the significance of lead acid battery used for starting and the powering of electrical systems in a commercial vehicle. In order to monitor the health of the battery, parameters SOC (State of Charge) and SOH (State of Heath) are introduced. The existing methods to calculate these parameters use impedance monitoring based approach which requires an expensive current sensor. This paper describes a smart algorithm and the experimental verification of the algorithm that uses only voltage values for predicting the failure of the battery. The voltage waveforms during a cranking event is studied by the ECU (Engine Control Unit) and the health of the battery is determined based on it. A parameter, SOH measure is obtained from the algorithm and the value of this parameter reduces with increase in life of the battery. If the value of the SOH measure reduces below a threshold, then the failure of the battery is predicted before the actual failure. The algorithm is validated with the help of real time data obtained from the vehicles. This method of calculating the SOH is resourceful and cost-effective as it exploits the data that’s already available in the ECU namely battery voltage and ambient temperature. Thus, it does not warrant an addition of sensor to the system in place.


Keywords: Lead acid battery; ECU (Engine Control Unit); SOH; Prognostic; Engine cranking

##plugins.themes.academic_pro.article.details##

How to Cite
R, A., & Prasad A.N, D. (2021). Prognostics and Health monitoring of Lead acid battery. ARAI Journal of Mobility Technology, 1(1), pp77–81. https://doi.org/10.37285/ajmt.1.0.10 (Original work published October 1, 2021)

References

  1. T. B. Reddy and D. Linden, Linden's handbook of batteries, New York: McGraw-Hill, 2011.
  2. R. Kerley, J. H. Hyun and D. S. Ha, "Automotive lead-acid battery state-of-health monitoring system," IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society, Yokohama, 2015, pp. 003934-003938, doi: 10.1109/IECON. 2015.7392714.
  3. Culpin, B. & Rand, David. (1991). Failure modes of lead/acid batteries. Journal of Power Sources. 36. 415-438. 10.1016/0378-7753(91)80069-A.
  4. D. Pavlov, Lead-acid batteries: science and technology: a handbook of lead-acid battery technology and its influence on the product. Amsterdam; Singapore: Elsevier Science Ltd., 2011.
  5. Lu, Rui et al. “Design of the VRLA Battery Real-Time Monitoring System Based on Wireless Communication.” Sensors (Basel, Switzerland) vol. 20, 15 4350. 4 Aug. 2020, doi:10.3390/s20154350
  6. Monitoring sealed automotive lead-acid batteries by sparse-impedance spectroscopy B HARIPRAKASH, S K MARTHA and A K SHUKLA* Solid State and Structural Chemistry Unit, Indian Institute of Science, Bangalore 560 012, India
  7. J. Marchildon, M. L. Doumbia and K. Agbossou, "SOC and SOH characterization of lead acid batteries," IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society, Yokohama, 2015, pp. 001442-001446, doi: 10.1109/ IECON.2015.7392303.
  8. V. Spath, A. Jossen, H. Doring and J. Garche, "The detection of the state of health of lead-acid batteries," Proceedings of Power and Energy Systems in Converging Markets, Melbourne, Victoria, Australia, 1997, pp. 681-686, doi: 10.1109/INTLEC.1997.646070.
  9. H. Chaoui, S. Miah, A. Oukaour and H. Gualous, "State-of-charge and state-of-health prediction of lead-acid batteries with genetic algorithms," 2015 IEEE Transportation Electrification Conference and Expo (ITEC), Dearborn, MI, 2015, pp. 1-6, doi: 10.1109/ITEC.2015.7165782.
  10. H. Sayeed, M. N. Al Subri Ivan, H. Ratiqul, E. M. Mahjabeen, A. F. Saykot and C. A. Hossain, "Lead Acid Battery Monitoring and Charging System for Backup Generators," 2019 International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST), Dhaka, Bangladesh, 2019, pp. 263-268, doi: 10.1109/ICREST. 2019.8644475.
  11. L. Zhen et al., "A novel comprehensive evaluation method for state-of-health of lead-acid batteries," 2018 International Conference on Power System Technology (POWERCON), Guangzhou, 2018, pp. 3765-3770, doi: 10.1109/POWERCON. 2018.8601795