UNIVERSITA’ DI PERUGIA – Engineering department

Advanced Battery Characterization and modeling

Keywords

Electrical Impedance Spectroscopy (EIS), Digital Twin (DT), System Identification (SI), multifrequency stimulus, real time characterization, State of Charge (SoC), State of Health (SoH)

Operation of the proposed solution

Advanced batteries are a key enabler of many innovative applications, including automotive, IoT based sensing, and powering of unmanned aerial vehicles (UAVs). Early warning of bettery deterioration is an important task, as it enables both predictive and and proactive maintainance, preventing battery failures during operations. Thus, the main goal of this activity is the development of advanced real time and non intrusive techniques for assessing the SoC and the SoH rechargeable battery. Lithium Ion Batteries are considered as the most significant Case Study. To this aim, low cost low power embedded hardware is being developed, featuring multifrequency stimuli to quickly assess the battery impedance at different frequencies, relating the measurement results to the battery SoC and SoH. Measurement results will be used to develop a Digital Twin, that, once connected to an electrical interface, based on a programmable impedance emulator, may appear as a true battery to a measuring instrument. Since testing of real battery involves time consuming charging and discarging cycles, this would permit the rapid prototyping and testing of embedded monitoring systems.

Challenges

1. Realizing a low-post low-power embedded device, running signal generation and estimation algorithms that feature a potentially large computational cost;
2. The estimation hardware needs to scan a frequency interval spanning over several decades;
3. The synthetized EIS multifrequency stimulus should excite all frequencies with a similar power.

Bibliography

1) Crescentini M., De Angelis A., Ramilli R., De Angelis G., Tartagni M., Moschitta A., Traverso P.A., Carbone P., “Online EIS and Diagnostics on Lithium-Ion Batteries by Means of Low-Power Integrated Sensing and Parametric Modeling,” (2021) IEEE Transactions on Instrumentation and Measurement, 70, art. no. 9224889, DOI: 10.1109/TIM.2020.3031185.
2) Santoni F., De Angelis A., Moschitta A., Carbone P., “Digital impedance emulator for battery measurement system calibration,” (2021) Sensors, 21 (21), art. no. 7377, DOI: 10.3390/s21217377.
3) De Angelis A., Ramilli R., Crescentini M., Moschitta A., Carbone P., Traverso P.A., “In-situ Electrochemical Impedance Spectroscopy of Battery Cells by means of Binary Sequences,” (2021) Conference Record – IEEE Instrumentation and Measurement Technology Conference, 2021-May, art. no. 9459998 DOI: 10.1109/I2MTC50364.2021.9459998.
4) Santoni F., De Angelis A., Moschitta A., Carbone P., “Analysis of the Uncertainty of EIS Battery Data Fitting to an Equivalent Circuit Model,” (2021) 6th International Forum on Research and Technology for Society and Industry, RTSI 2021 – Proceedings, pp. 497 – 501, DOI: 10.1109/RTSI50628.2021.9597288.
5) Carbone P., Angelis A.D., Santoni F., Moschitta A., “Measurement of the Parameters of Multiple Sinusoids Based on Binary Data,” (2021) IEEE Transactions on Instrumentation and Measurement, 70, art. no. 9239262, DOI: 10.1109/TIM.2020.3033074.
6) De Angelis G., De Angelis A., Moschitta A., Carbone P., Pintelon R., “Online Identification of the LC Product in Coupled Resonant Circuits,” (2020) IEEE Transactions on Instrumentation and Measurement, 69 (7), art. no. 8887191, pp. 4592 – 4603, DOI: 10.1109/TIM.2019.2950583.
7) Moschitta A., Comuniello A., Santoni F., De Angelis A., Carbone P., Fravolini M.L., “Statistically Efficient Simultaneous Amplitude Measurement of Multiple Linear Chirp Signals,” (2021) IEEE Transactions on Instrumentation and Measurement, 70, art. no. 9323044, DOI: 10.1109/TIM.2021.3051667.

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