@article{kim_balagopal_kerrigan_garcia_chow_bourham_fang_jiang_2023, title={Noninvasive liquid level sensing with laser generated ultrasonic waves}, volume={130}, ISSN={0041-624X}, url={http://dx.doi.org/10.1016/j.ultras.2023.106926}, DOI={10.1016/j.ultras.2023.106926}, abstractNote={This article proposes a noninvasive liquid level sensing technique using laser-generated ultrasound waves for nuclear power plant applications. Liquid level sensors play an important role of managing the coolant system safely and stably in the plant structure. Current sensing techniques are mostly intrusive, performing inside the fluidic structure, which is disadvantageous in terms of the regular maintenance of the plant system. Furthermore, typical intrusive sensors do not perform stably under varying environmental conditions such as temperature and radiation. In this study, sensing units are attached to the outer surface of a liquid vessel to capture guided ultrasound waves in a nonintrusive manner. The signal intensity of the guided wave dissipates when the signal interacts with the internal liquid media. The sensing mechanism is mathematically expressed as an index value to correlate the liquid level with the sensor signal. For the acoustic wave generation, laser-generated ultrasound was adopted instead of using typical contact type transducers. Following the simulation validation of the proposed concept, the performance of the developed sensor was confirmed through experimental results under elevated liquid temperature conditions. The nonlinear multivariable regression exhibited the best-fit to the datasets measured under the variable liquid level and temperature conditions.}, journal={Ultrasonics}, publisher={Elsevier BV}, author={Kim, Howuk and Balagopal, Bharat and Kerrigan, Sean and Garcia, Nicholas and Chow, Mo-Yuen and Bourham, Mohamed and Fang, Tiegang and Jiang, Xiaoning}, year={2023}, month={Apr}, pages={106926} }
 @article{balagopal_chow_2020, title={The Physical Manifestation of Side Reactions in the Electrolyte of Lithium-Ion Batteries and Its Impact on the Terminal Voltage Response}, volume={6}, ISSN={["2313-0105"]}, DOI={10.3390/batteries6040053}, abstractNote={Batteries as a multi-disciplinary field have been analyzed from the electrical, material science and electrochemical engineering perspectives. The first principle-based four-dimensional degradation model (4DM) of the battery is used in the article to connect the interdisciplinary sciences that deal with batteries. The 4DM is utilized to identify the physical manifestation that electrolyte degradation has on the battery and the response observed in the terminal voltage. This paper relates the different kinds of side reactions in the electrolyte and the material properties affected due to these side reactions. It goes on to explain the impact the material property changes has on the electrochemical reactions in the battery. This paper discusses how these electrochemical reactions affect the voltage across the terminals of the battery. We determine the relationship the change in the terminal voltage has due to the change in the design properties of the electrolyte. We also determine the impact the changes in the electrolyte material property have on the terminal voltage. In this paper, the lithium ion concentration and the transference number of the electrolyte are analyzed and the impact of their degradation is studied.}, number={4}, journal={BATTERIES-BASEL}, author={Balagopal, Bharat and Chow, Mo-Yuen}, year={2020}, month={Dec} }
 @inproceedings{balagopal_huang_chow_2018, title={Effect of calendar ageing on SEI growth and its impact on electrical circuit model parameters in lithium ion batteries}, DOI={10.1109/ieses.2018.8349846}, abstractNote={This paper discusses the effect of calendar aging on the growth rate of SEI. It discusses the reasons for the growth of SEI and the implementation of SEI growth in the 3D First Principle Based Degradation Model (3DM) of the battery. The growth of SEI is simulated over a period of 3 years and the impact it has over the terminal voltage and current generated by the battery are plotted and discussed. The results are then applied to the Equivalent Circuit Model (ECM) of the battery to study and identify the impacts that calendar aging and SEI growth has on the parameters of the circuit. The increase in the internal resistance and the decrease in the capacity are also discussed.}, booktitle={2018 IEEE International Conference on Industrial Electronics for Sustainable Energy Systems (IESES)}, author={Balagopal, B. and Huang, C. S. and Chow, M. Y.}, year={2018}, pages={32–37} }
 @inproceedings{salamati_huang_balagopal_chow_2018, title={Experimental battery monitoring system design for electric vehicle applications}, DOI={10.1109/ieses.2018.8349847}, abstractNote={Li-ion batteries are considered as main energy sources for next generation of transportation systems. This paper presents a systematic way to design an efficient hardware testbed for Battery Monitoring System (BMS) applications in Electric Vehicle (EV) industry following the standard industrial communication protocol. The hardware testbed performs both the battery voltage/current data acquisition and the Co-Estimation algorithm. Co-Estimation is an electric circuit model based SOC estimation algorithm which takes model parameter variations into account. In this paper, the Co-Estimation algorithm is firstly discussed. A battery hardware testbed design is then elaborated, and reasons for selecting main components, including microcontroller and voltage/current sensors are explained. The performance of the hardware testbed is compared with MATLAB simulation result using the same Co-Estimation algorithm, showing similar performance between two different platforms: hardware testbed and software simulation.}, booktitle={2018 IEEE International Conference on Industrial Electronics for Sustainable Energy Systems (IESES)}, author={Salamati, S. M. and Huang, C. S. and Balagopal, B. and Chow, M. Y.}, year={2018}, pages={38–43} }
 @inproceedings{balagopal_huang_chow_2017, title={Effect of calendar aging on Li ion battery degradation and SOH}, DOI={10.1109/iecon.2017.8217340}, abstractNote={This paper discusses the impact of calendar ageing on the anode and the concentration of lithium ions in the anode structure. It discusses the modeling of the calendar ageing, its implementation in the 3D First Principle Based Degradation Model (3DM) of the battery and the results that were observed as a result of calendar ageing over a period of 4–6 years. The paper also relates these physical degradation phenomena with the impact that they have on the parameters of the Equivalent Circuit Model of the battery. The paper uses the capacity degradation and the increase in the internal resistance of the battery to showcase the impact of calendar ageing on the State of Health of the battery.}, booktitle={Iecon 2017 - 43rd annual conference of the ieee industrial electronics society}, author={Balagopal, B. and Huang, C. S. and Chow, M. Y.}, year={2017}, pages={7647–7652} }
 @inproceedings{balagopal_chow_2016, title={Effect of Anode Conductivity Degradation on the Thevenin Circuit Model of Lithium Ion Batteries}, DOI={10.1109/iecon.2016.7793429}, abstractNote={This paper proposes a high resolution anode degradation model of the lithium ion battery based on its physics of operation in 3D and in layers. This model is developed in a multiphysics software called COMSOL and in Matlab. This paper describes the procedure followed to develop the model in 3D and the features of this model. The performance of the model is validated with experimental data obtained from a battery of the same chemistry and capacity. The paper will then relate the effect of the degradation of the anode conductivity on the Thevenin Circuit Model parameters. The established relationship can help identify the parameters that are important for battery degradation and will be invaluable for real-time and online estimation of SOH and SOF of the battery.}, booktitle={Proceedings of the iecon 2016 - 42nd annual conference of the ieee industrial electronics society}, author={Balagopal, B. and Chow, M. Y.}, year={2016}, pages={2028–2033} }
 @inproceedings{balagopal_chow_2015, title={The state of the art approaches to estimate the state of health (SOH) and state of function (SOF) of lithium ion batteries}, DOI={10.1109/indin.2015.7281923}, abstractNote={This paper discusses the commonly used techniques to estimate the state of health (SOH) and state of function (SOF) of lithium ion batteries and their limitations. Factors affecting the health and SOF of the battery are discussed in this paper. The SOH of the battery is mainly represented by the capacity degradation and the increase in the internal resistance. The other indices that could represent the battery's health are also briefly discussed. The different techniques that are used to estimate the capacity and internal resistance of the battery are discussed along with their limitations. The concept of SOF and its relationship with SOC, SOH and temperature are discussed along with the commonly used techniques to estimate the SOF of the battery. This paper also discusses the limitations in the definition and estimation of the SOF.}, booktitle={Proceedings 2015 ieee international conference on industrial informatics (indin)}, author={Balagopal, B. and Chow, M. Y.}, year={2015}, pages={1302–1307} }
 @inproceedings{rahimi-eichi_balagopal_chow_yeo_2013, title={Sensitivity Analysis of Lithium-Ion Battery Model to Battery Parameters}, DOI={10.1109/iecon.2013.6700257}, abstractNote={Different models have been proposed so far to represent the dynamic characteristics of batteries. These models contain a number of parameters and each of them represents an internal characteristic of the battery. Since the battery is an entity that works based on many electrochemical reactions, the battery parameters are subject to change due to different conditions of state of charge (SOC), C-rate, temperature and ageing. Referring to our previous work on online identification of the battery parameters, the change in the parameters even during one charging cycle is an experimental fact at least for many lithium-ion batteries. In this paper, the terminal voltage is used as the output to investigate the effect of changes in the parameters on the battery model. Therefore, we analyze the sensitivity of the model to the parameters and validate the analysis by comparing it with the simulation results. Since the output of the model is one of the main components in estimation of the state of charge (SOC), the sensitivity analysis determines the need to update each of the battery parameters in the SOC estimation structure.}, booktitle={39th annual conference of the ieee industrial electronics society (iecon 2013)}, author={Rahimi-Eichi, H. and Balagopal, B. and Chow, M. Y. and Yeo, T. J.}, year={2013}, pages={6794–6799} }