Measurement Of Internal Resistance Research Articles

Estimation of Lithium-Ion Battery Health in Electric Bicycles Using Internal Resistance Measurement Method

This study evaluates the performance of a 36 Volt 10 Ah battery in an electric bicycle with a 350-Watt Brushless DC (BLDC) motor as an environmentally friendly alternative to overcome the negative impacts of motorized vehicle use in Indonesia. In addition, this study measured the State of Health battery’s value of internal resistance, which is different from other studies that use capacity fading. With a focus on maximum travel distance and travel time, experiments were conducted without load and with a 70kg load. The no-load test was conducted only once, resulting in a travel time of 600 minutes and a distance of 330.1 Km. Although the battery was not discharged, the results were not in line with expectations, so the no-load test was only conducted once. In the 70kg load test, six trials were conducted with variable measurements of distance, battery voltage, and battery resistance. Results showed variations in distance between 50.7 km and 53.1 km, and travel time between 151 and 160 minutes. The battery voltage varied from 31.316 Volts to 31.850 Volts. The resistance in the battery also showed an increase of about 0.0001 ohms from 0.1132 ohms to 0.1139 ohms. Overall, the results from the study showed that as time and usage progressed, the battery voltage and internal resistance values tended to increase, while the distance and travel time tended to decrease. The internal resistance measurement method proved to be effective in assessing battery health as the State of Health value decreased throughout the experiment.

Evaluation Method of Internal Resistance for Repurposing Using Middle and Large-Sized Batteries

The number of used batteries is expected to dramatically increase in the near future due to the expansion of the electric vehicle (EV) market globally. Accordingly, the Korean government has improved the supporting structures for the recycling system for used batteries, and in particular, in the field of repurposing, various studies are being conducted with a focus on effective evaluation methods that can secure the performance and safety of batteries after use. The repurposing of used batteries is mostly adapted in the field of energy storage systems for normally used EV batteries and a total inspection before repurposing is required due to battery characteristics that can vary depending on the operational environments of and accidents involving medium- and large-sized batteries for EVs and energy storage systems (ESSs) that have been occurring continuously for the past few years. Therefore, this paper investigates the operating mechanisms of the internal resistance test method and implements a test device for middle- and large-sized cells and packs. Based on the proposed test method, the internal resistance of nickel manganese cobalt (NMC)-type commercial large batteries is analyzed according to the SOC (state of charge), SOH (state of health), ambient temperature, and connection degradation of batteries. The distribution degrees of the alternative current (AC) internal resistance (IR) and direct current (DC) internal resistance (IR) measurement methods under state of health (SOH) test conditions are about 7% and 50%. It was found that the DC IR measurement method is more effective in diagnosing battery cell degradation. The distribution degree of DC IR measurements for the degraded connection condition shows an increase of less than 1% regardless of the state of charge (SOC), while the distribution degree of the AC IR measurements shows an increase of up to 319%, indicating that the AC IR method is more effective than the DC IR method in identifying connection degradation. It is confirmed that the proposed method is effective in internal resistance measurement and safety evaluations for the repurposing of batteries.

In Situ Measurement of Dynamic Internal Short Circuit Resistance during Nail Penetration of Lithium-Ion Cells and its Implications on Cell Robustness and Abuse Tolerance

Here we report a method for in situ measurement of internal short circuit (ISC) resistance during nail penetration testing of lithium-ion cells. The method is demonstrated with dry cells, wet dummy cells, and working cells using a small nail and slow penetration speed. ISC current and ISC temperature are also measured during the tests. It is confirmed that the ISC resistance changes dramatically, by several orders of magnitude, during nail penetration. More importantly, it is found that the stable resistance after full penetration is much higher than the lowest dynamic resistance at earlier stages of nail penetration. Analysis based on such a stable ISC resistance would underestimate the risk of thermal runaway during nail penetration tests. It is also found that ISC in some cases may be mitigated due to melting or rupture of aluminum foil surrounding the nail, implying a mechanism that may be able to be used towards the design of more robust/abuse tolerant Li-ion cells. Lastly, it is found that nail penetration using a larger nail reduces ISC resistance during penetration of cells but the general behaviors of ISC resistance are similar to those during smaller nail penetration.

An SMPS-Based Lithium-Ion Battery Test System for Internal Resistance Measurement

A switching mode power supply (SMPS)-based lithium-ion (Li-ion) battery test system (BTS) is proposed to meet the increasing demands of tests in battery research. To improve the flexibility, while building the BTS with low cost and high reliability, an SMPS is employed as a charger/discharger, combined with a digital-to-analog hybrid control system to regulate its output voltage and current. Based on the BTS, two dc internal resistance (DCIR) measurement methods are designed, and a battery state classification method based on the DCIR cluster analysis with similarity as the judgment basis is proposed. An experimental prototype is developed to verify the feasibility of the proposed BTS and methods. The results show that the BTS possesses excellent voltage and current regulation capabilities for charging, discharging, and grid energy recovery. The internal parameter extraction method enables obtaining DCIR and other parameters with high accuracy. The online measurement method allows automatic acquisition of real-time DCIR and its variation trend without affecting the charging, which greatly improves the measurement efficiency. The proposed hierarchical clustering method based on DCIR effectively achieves the classification of battery states with excellent practicality and robustness.

Electrochemical lithium storage performance at high voltage and temperature of LiNi0.6Co0.2Mn0.2O2 cathode for Lithium-ion batteries by facile Mn3(PO4)2 dry coating

Herein, we successfully synthesized the Mn3(PO4)2-coated LiNi0.6Co0.2Mn0.2O2 (MP-NCM) by the dry coating method, which is facile to apply to industrial applications. MP-NCM has improved electrochemical performance and storage properties compared to the bare sample under a high voltage cut-off condition of 4.55 V and a high-temperature environment of 60℃. MP-NCM exhibited a discharge capacity of 198.5 mAh g−1 and capacity retention of 96.6 % after 50 cycles at 60 °C with an electrode loading level of 11 ± 0.2 mg cm−2, and higher capacity retention of 70 % after storage. Remarkably, according to the direct current internal resistance (DCIR) measurement, MP-NCM showed an increased rate of resistance, which is 47 % and 40.2 % points lower than the bare sample in the charging and discharging modes respectively. The MP coating treatment introduced not only reduces cation-mixing by reconstructing the layered structure of the particle surface according to the doping of stable manganese ions but also serves to stabilize the surface according to the formation of Li3PO4.

(Digital Presentation) In Situ Measurement of Internal Short Circuit Resistance during Nail Penetration of Lithium-Ion Cells

Internal short circuit (ISC) is one of the main causes of lithium-ion cell thermal runaway in field failures. Nail penetration has been widely used to trigger ISC for evaluation of thermal runaway risks. Previous modeling studies1 , 2 revealed that ISC resistance greatly influences heat generation and thermal runaway risk, but there are few reports on experimental measurement of ISC resistance during nail penetration3. Furthermore, ISC resistance was assumed to be constant in these modeling and experimental studies. However, our recent experiments4 , 5 suggested that ISC resistance changes dramatically during nail penetration. Therefore, it is important to measure the dynamic ISC resistance in situ during nail penetration of lithium-ion cells. Such measurement will help better understand if and how an ISC triggers thermal runaway. The experimental data will also be useful for validation and improvement of numerical models on lithium-ion cell nail penetration.In this study we report a method for in situ measurement of dynamic ISC resistance during nail penetration. As shown schematically in Figure 1, a small test lithium-ion cell made of single unit of electrodes and four tabs are developed. Two tabs are connected to a large power supply lithium-ion cell through a low-resistance current sensor. The other two tabs are connected to a voltage sensor for measurement of test cell voltage. Then the test cell is penetrated using a small, slow and in situ sensing (3S) smart nail as reported in our earlier work4 , 5. A picture of such smart nail is shown in Figure 1. When an ISC is formed inside the test cell by the smart nail, external current will flow from the large power supply cell to the test cell. If the test cell is much smaller than the large power supply cell in dimension and capacity, it is assumed that the measured current is approximately equal to the ISC current and the measured test cell voltage (V2 in the schematic) approximately equal to the ISC voltage. Then the ISC resistance can be obtained through dividing the ISC voltage with the ISC current.Figure 2 and Figure 3 show preliminary results of this study based on dry test cells without electrolyte. The cells were penetrated using a smart nail with outer diameter of 0.76 mm at a speed of ~0.03 mm/s. At the tip of the nail, a thermocouple with diameter of 0.5 mm was embedded for in situ measurement of ISC temperature. The area of cathode in the test cells is 10 mm by 10 mm with a nominal capacity of 1.8 mAh. The large power supply cell has a nominal capacity of 3,000 mAh. Figure 2 shows results of penetration from Al foil to Cu foil while Figure 3 shows results of penetration from Cu foil to Al foil. It can be seen that ISC resistance changed dramatically during nail penetration in both cases. The lowest ISC resistance was several orders of magnitude lower than the stable resistance after full penetration. The lowest ISC resistance also caused rapid increase of ISC temperature, indicating higher risk of thermal runaway. By comparing Figure 2 and Figure 3, a stable resistance after full penetration was similarly seen in the two cases, but the dynamic resistance responses were very different. The dynamic resistance can be attributed to the different resistivity of test cell components as well as the change of contact resistance between the nail and those components. Moreover, the lowest ISC resistance during penetration from Al to Cu is tens of times smaller than that during penetration from Cu to Al. These results provide new insights into nail penetration processes. They also imply that future modeling studies on nail penetration should consider the dynamic change of ISC resistance to more accurately reflect the physical behaviors. More details about these dry test cell results and new results of working test cells with electrolyte will be presented in the conference. References W. Zhao, G. Luo and C.-Y. Wang, Journal of The Electrochemical Society, 162, A207 (2014).T. Yamanaka, Y. Takagishi, Y. Tozuka and T. Yamaue, Journal of Power Sources, 416, 132 (2019).M. Chen, Q. Ye, C. Shi, Q. Cheng, B. Qie, X. Liao, H. Zhai, Y. He and Y. Yang, Batteries & Supercaps, 2, 874 (2019).S. Huang, X. Du, M. Richter, J. Ford, G. M. Cavalheiro, Z. Du, R. T. White and G. Zhang, Journal of The Electrochemical Society, 167 (2020).S. Huang, Z. Du, Q. Zhou, K. Snyder, S. Liu and G. Zhang, Journal of The Electrochemical Society, 168 (2021). Figure 1

(Digital Presentation) Develop Cell Internal Resistance Measurement Tool As a Lib Cell Characterization Technology

As LiB cell is not a pure ohmic device but a complex electrochemical device with capacitive and inductive behaviors, its characteristic and performance will vary depending on the input signals, frequencies, and usage conditions. And as LiB cell is a non-linear system, its internal resistance (IR) depends significantly on variables, like aging (state of Health: SOH), state of charge (SOC), temperature, applying current rate and period. The IR is an intrinsic property of a cell representing its characteristic, performance, and health status at the measuring point. Therefore, its precise measurement is essential for its usage for cell characterization, quality control (QC), and grading-selection criteria for designing cell, module, pack, host system, and thermal management, health monitoring-prediction criteria. However, IR measurement is inherently complex and requires sophisticated procedures (1,2). Direct wave DC pulse and AC electrochemical impedance spectroscopy (EIS) are the prevalent techniques used for cell IR characterization (1,2). Most cell QC processes use the AC-impedance tool at 1.0 kHz with voltage, and IEC-62660 adopt a DC pulse, Hybrid Pulse Power Characterization (HPPC) method, and new proposals, like a multisine signals method and a pulse-multisine, have been proposed (1,2). However, the AC-impedance tool (1.0 kHz) cannot represent the dynamic behaviors of the cell and system compared to the DC pulse (3). In addition, some DC pulse test requires pre-testing conditions and a long test period; furthermore, there is no harmonized test technologies among the battery standards and some best practices of the LiB cell testing and characterization. To adopt a test method and condition as a QC tool for cell characterization that should be simple and not be time-consuming on pre-measurement condition and testing procedure to perform (3).This research aims to propose simple IR measurement tools in which test results are comparable with each other’s and do not require a long period of pre-test conditioning time and a time-consuming test period. We evaluated four test methods of the cell IR measurement at four temperature conditions (0 ~ 5 ℃, RT (20 ~ 25 ℃), 35 ℃, and 45 ℃). In addition, we selected five types of cell groups (two 18650 cells, two pouch-type cells, and one prismatic cell) to evaluate the IR. The four IR measurement test methods are classified with DC pulse tools (simplified DC pulse method and HPPC) and AC pulse signal tools (Full range EIS and AC-pulse Impedance at 1.0 kHz). Test results studied the relationship between cells’ IR response behaviors by each type of pulse and the electrochemical mechanism of the cells. After comparing those test results, the best IR characterization tool and procedure will be proposed as a standard LiB cell characterization technology.We found the simplified DC pulse method is simple and not time-consuming on both pre-test condition and testing procedure to perform and provide reasonable dynamic behaviors of the cell system compared to other methods. Figure 1 shows the trends of cell IR changes according to the experimental variables, applied current rate and frequency from the simplified DC pulse method. The blue color dot zone shown the optimum applied current rate and frequency and the red color dot zone shown the optimum frequency (3).Reference:1) Thomas R. B. Grandjean, Jakobus Groenewald, Andrew McGordon, Widanalage D. Widanage and James Marco, Batteries 2018, 4, 49; doi:10.3390/batteries4040049.2) Mohammad A. Hoque, Petteri Nurmi, Arjun Kumar, Samu Varjonen, Junehwa Song, Michael G. Pecht, Sasu Tarkoma Journal of Power Sources 513 (2021) 2305193)3) Jaesik Chung, Kwang Jung, and Giovanni Flores, 2020 NASA Aerospace Battery Workshop November 17 ~ 19 2020 Figure 1

Effects of temperature on the ohmic internal resistance and energy loss of Lithium-ion batteries under millisecond pulse discharge

Battery energy storage technology has a promising future in the field of compact high-power pulse drivers due to its high energy storage density. In this paper, three types of high-performance lithium batteries, such as lithium titanate (LTO) battery, lithium iron phosphate (LFP) battery, and Ni,Co,Al (NCR) ternary lithium-ion battery, have been studied in different ambient temperatures by using DC internal resistance measurement method. The result shows that the ohmic internal resistance of lithium batteries increases when the temperature drops. When the temperature is above -30 °C, the ohmic internal resistances of the three types of battery are nearly identical. At -50 °C, the ohmic internal resistances of LFP battery and LTO battery are about 83 mΩ and 151 mΩ, respectively, and the ohmic internal resistance of NCR li-ion battery increases by one order of magnitude. The energy loss from LTO battery and LFP battery during pulse discharge is similar. In the temperature range of -30 °C to 50 °C, the energy loss of NCR li-ion battery pulse discharge is the largest. At -50 °C, the energy loss of NCR li-ion battery is the least.

民生二次電池の内部抵抗に基づく超小型衛星搭載バッテリーの状態推定の最適化

We demonstrated the feasibility of an on-orbit charge/discharge simulation for an electric power system of CubeSats based on the internal resistance of a commercial cylindrical lithium-ion battery (LIB), which will be installed in the several CubeSats by two kinds of measurements: electrochemical impedance spectroscopy (EIS) and current-rest-method (CRM). Both simulations of SOC based on the internal resistance derived from EIS and CRM were in close agreement with the respective SOC behavior obtained by hardware simulators, indicating that accuracy of the simulations. Furthermore, we also discussed the effects of the internal resistance measurement on the battery state estimation. Meanwhile it was found that the deep consideration of the variation in internal resistance due to cell operation is required to realize an accurate on-orbit simulation, thus further optimization of the simulation with taking account the heat generation during battery operation is required to realize accurate battery management of the electric power supply for CubeSats.

Design of Remote Monitoring System for Substation DC Power Supply under the Background of Big Data

The DC power supply(DPS) system is an important part of the substation. In order to adapt to the current unmanned operation and maintenance mode of the substation and the new requirements of state maintenance and management, it must develop in the general direction of digitalization, programming and intelligence. To ensure the safety and stability of the new operation and maintenance mode of the power system. Through the design and application research of the DPS remote monitoring system of the substation, the real-time data collection of the domestic DPS device is realized, the collected data information is summarized, and the cooperation of the remote control center and related operation and maintenance management teams is requested. The management software effectively analyzes the collected equipment operating parameters and real-time data, extracts fault information and hidden dangerous data required for operation and maintenance, which is helpful for the scientific management and risk prediction of DC power equipment in substations. The operation and maintenance personnel and the DPS system of the substation ensure the operation in a high-quality and healthy state and the safe and stable operation of the entire power network. This paper studies the design principle, structure and function of the DPS remote monitoring system used in the substation. On this basis, in-depth study of battery voltage equalization technology, internal resistance measurement technology and other core technologies related to DPS remote monitoring system design. In order to realize the online monitoring, analysis and diagnosis of the operation information data of DPS devices such as remote charging and discharging operation safety management strategy, DC power information collection and communication network design, the theoretical and technical foundations have been formulated.

Redox Stability of Tubular Solid Oxide Cell Using LaGaO3 Electrolyte Film Prepared by Dip-Coating

Reversible operation of SOFC is now important subjects from energy storage of renewable electric power from solar or wind power. At present, planer type cell design is widely used for this purpose, however, because of tight gas sealing, tubular type cell design is more suitable. In this study, tubular solid oxide cell using La0.9Sr0.1Ga0.8Mg0.2O3−δ (LSGM) thin electrolyte film was prepared by dip-coating and co-sintering process. NiO-YSZ porous substrate with 10 mm diameter and 30 mm length was used for preparation of the cell. For preventing reaction between LSGM and NiO, TiO2-Ce0.6La0.4O2/Ce0.6Mn0.3Fe0.1O2 was used for buffer layer. The cyclic operation of fuel cell and electrolysis mode was measured for investigating the stability of the prepared tubular cell at an intermediate temperature of 600℃ under the fuel of 20%steam-30%H2 in Ar. After 100 redox cycles under the applied current density of ±100 mA cm-2 , OCV was almost the same with the initial value before measurement. The terminal potential in SOFC operation became slightly lower and unstable with increasing cycle number, however, degradation in power density is not significantly observed. The cell also presents a relative stable performance in the electrolysis mode and it seems to be more active to SOEC than that to SOFC. From measurement of internal resistance, degradation may be related with the increased overpotential of anode. Therefore, aggregation and reoxidation of Ni in Ni-YSZ substrate is expected.In order to further increase performance of the cell, effects of Ce infiltration into NiO-YSZ contributes and it was found that the power density and electrolysis performance was much increased by the decreased internal resistance. The redox stability of NiO-YSZ-CeO2 cell was also measured and it also presents a stable redox performance after 100 times cycles by infiltration of CeO2.

Accurate measurement of internal resistance in microbial fuel cells by improved scanning electrochemical impedance spectroscopy

In this study, a scanning electrochemical impedance spectroscopy (EIS) technique is proposed to confirm the variation of internal resistance (Rint) including charge transfer resistance (Rct) and ohmic resistance (Rohm) under various working conditions of microbial fuel cells (MFCs). In order to establish a scanning EIS method, overall Rint of the system and Rct of anode and cathode were measured by EIS under various external resistance conditions. Using this method, it was confirmed that the Rohm and Rct of each electrode changed variably. Based on the use of scanning EIS, the rapid increase in the Rct of anode was found to be the main cause of a power-overshoot. As such, the use of scanning EIS is a methodology that can provide data to understand undesirable phenomena such as power-overshoot and voltage reversal which are generated by the typical operational characteristics of MFCs when used in scale up experiments. The use of scanning EIS should be applied as a novel measurement technique that improves on the use of the open circuit mode based EIS methods.

Log-Linear Model for Predicting the Lithium-ion Battery Age Based on Resistance Extraction from Dynamic Aging Profiles

In this article, we propose a method for extracting, modeling, and predicting the resistance of Lithium-ion batteries directly from the battery dynamic mission profile. While the extraction of the mainly relied on data manipulation and bookkeeping, the modeling and subsequent prediction of the resistance used a log-linear model. It is shown that the estimated log-linear model can be used to create a posterior probability distribution of the age of the battery, given an internal resistance measurement and the state-of-charge (SOC) value at which it was measured. This distribution was used calculate the expected age of the battery, and the expected age was compared to weekly check-ups. At an SOC of 80% a mean absolute error (MAE), between the weekly check-ups and the expected age, of 5.83 weeks [706 full equivalent cycles (FEC)] was achieved. Furthermore, it is shown that by introducing a decision threshold the MAE could be reduced as far as 2.65 weeks (321 FEC). Finally, a method is introduced for handling cases where the SOC was not known exactly.

Dynamic Heat Generation of LiNi0.5Co0.2Mn0.3O2 Half Cell Under Cycling Based on an In Situ Micro-calorimetry

To further understand the thermal properties of lithium ion batteries, in situ measurement and calculation of the heat generation under operating condition are conducted. In this work, a novel micro-calorimeter with high accuracy is applied to study the heat flow of the LiNi0.5Co0.2Mn0.3O2/Li half cell. The dynamic heat generation and corresponding electrochemical data are detected out under isothermal environment from 30°C to 70°C with different current rates (0.2, 0.4, 0.6, 0.8 and 1.0 C) and electrode thicknesses (400, 200 and 100 μm). In addition, heat generation rate is calculated based on the measurement of entropy coefficient and internal resistance. It is found that the heat generation rises with the increase of thickness and current rate, due to concentration polarization and electrochemical polarization, respectively. The lithiation process is more sensitive to changes in current rate than delithiation. Appropriately increasing the temperature can improve the activity of material and reduce the energy consumption of the battery. Besides, the contribution of reversible heat to the overall heat generation should be taken into account especially at a lower current rate (< 0.5 C). The detailed analysis of heat generation and electrochemical performance can provide accurate data for thermal management systems.

Overcharge and Aging Analytics of Li-Ion Cells

Overcharge presents a serious safety concern for large scale applications of Li-ion batteries. Despite the availability of several studies of aging-induced and overcharge-induced degradation, there still exists a knowledge gap of what would happen if both degradation mechanisms simultaneously occur. In this work, commercial graphite/LCO pouch cells (5 Ah) are continuously cycled at different upper cutoff voltages, 4.2 through 4.8 V, to elucidate the cumulative effect of the overcharge process on the long-term cycling. As the upper cutoff voltage is extended, the cell gains a higher initial capacity but the cycle life diminishes significantly. Cells overcharged beyond 4.5 V experience significant volume expansion and a high rate of capacity fade, as well as a considerable increase in the temperature and internal resistance. Lithium plating and electrolyte decomposition are observed in cells charged beyond 4.5 V, with SEM-EDS verifying their presence. Electrochemical evidence of both degradation modes appears as a voltage undershoot in the discharge curves. A comparative study of various State of Health (SoH) estimation parameters is presented with the introduction of a new dimensionless SoH indicator, ΦR, based on internal resistance measurement. The proposed degradation number is found to be a good indicator of aggravated degradation in Li-ion cells.

A New State of Health Diagnosis Method Utilizing Self-Supervised Deep Learning Via Virtual Tests

For state of the art State of Health (SoH) diagnosis methods a lot of domain-specific expertise and experimental data is needed. Utilizing parameter estimation methods like Kalman filters, the internal resistance and capacity may be estimated. Those methods require a battery model that fits to the battery and the desired application. Established Machine learning methods on the other hand exchange that need of domain knowledge against the need of extensive laboratory experimentation data. This work proposes a new machine learning method for SoH diagnosis that minimizes the amount of required laboratory data while taking no assumptions about the battery chemistry and parameters. The method solely depends on the during operation directly measurable quantities voltage and current with no need of estimating State of Charge. This self-supervised learning approach is enabled by the concept of virtual tests. Virtual tests apply standardized laboratory methods like current pulse tests for internal resistance measurement to a machine learning model. That machine learning model imitates the behavior of the battery by estimating the terminal voltage in dependency of the current, therefore mitigating the need for labeled SoH data. This self-supervised learning method allows an online adaptation of the model to changes of behavior of the aging battery while being used in the working environment. For example for estimating the internal resistance of a traction battery in a battery electric vehicle the current and voltage profiles may be measured while everyday driving.[Figure 1] A machine learning model maps the measured current profile to the voltage profile, therefore memorizing the battery dynamics. Because the model needs to track internal states that represent this dynamic and state of charge a recurrent neural network is a good fit for that application. When the model is trained on the data, a rectangular current profile will be applied to the model, representing a virtual pulse test. The internal resistance can be calculated out of the applied current and the voltage drop of the estimated voltage profile.[Figure 2] In the same way a constant current discharge may be applied for capacity estimation purposes. Later, when the state of health degenerated further, the existing model may be trained on more recent data in order to update the SoH. Figure 3 visualizes the described process. This new method allows the estimation of the SoH with neither specific knowledge about the battery nor elaborate experimental aging data of many instances of the same battery. Instead it utilizes established laboratory methods as is described, for instance, in ISO 12405-4:2018. That way it also does not rely on labeled SoH values for training of the model. Also the accuracy of the method does not suffer from a drift error that increases with the age of the battery. These advantages make it particularly suitable for low quantities and prototypes where extensive laboratory experiments are too expensive or demand too much time. This work was funded by the German Federal Ministry of Education and Research (BMBF, Funding number: 16EMO0262). Figure 1

Sensor Design for Four-Electrode Electrical Resistance Tomography With Voltage Excitation

Electrical resistance tomography (ERT) is used to image conductivity distributions. Most existing ERT systems are based on a current-excitation and voltage-detection to measure resistance with the use of small pin electrodes. This measurement technique has several limitations, like the existence of a severe fringe effect. This generates image distortion and no quantitative data can be acquired. In addition, the conventional ERT systems are not able to image stratified flows. The ERT systems using voltage-excitation and current-detection (VECD) with large rectangular electrodes were proposed, overcoming the limitations of conventional ERT. The VECD technique can reduce image distortion due to smaller fringe effect and allows imaging stratified flows. In the past, the two-electrode sensing technique was used without careful consideration of parasitic resistance, as the contact impedance. This paper presents a design of ERT with voltage excitation with a four-electrode sensor structure to reduce the effect of the contact impedance, the resistance of the switching stage, and the wiring on the internal resistance measurement. The simulation and experimental results with different conductivity distributions show the superior performance of the proposed structure.

(Keynote) Developing Safe Sodium-Ion Battery Technology for Stationary Storage Applications

Sodium-ion batteries (NIBs) have been emerging as one of the most promising candidates for stationary storage applications such as telecommunication towers, micro-grids etc., mainly because Na is one of the most abundant elements on the Earth’s crust.1,2 NIB operating at ambient temperature is expected to be durable, safe and inexpensive. Regardless of the relatively lower energy density of NIBs, they can be effectively employed for stationary applications, where the weight and footprint requirements are not severe.3 However, identifying appropriate anode, cathode, electrolyte, as well as the combination of these three components have always been challenging to develop robust NIB.4,5 In this talk, we will present investigation of the storage performance, thermal stability6 and SEI layers of four notable anodes, viz., hard carbon, graphite, TiO2 and Na2Ti3O7 7 using ether-based non-flammable electrolyte: 1M NaBF4 in tetraglyme and compare with the results obtained with commonly used carbonate-based electrolyte: 1M NaClO4 in EC:PC. We report better storage performance with higher first cycle coulombic efficiency of above anodes tested against metallic Na using ether-based electrolyte compared to carbonate-based electrolytes. Thermal studies, ATR-FTIR and impedance spectroscopy recorded at fully sodiated and fully desodiated states of these four anodes further confirm that a more stabilized SEI is formed by ether-based electrolyte. Above studies further suggests that the ether-based electrolyte is much safer for NIBs compared to carbonate-based electrolytes such as 1M NaClO4 in EC:PC. For the cathode, Na3V2(PO4)3 (NVP) was chosen due to a high redox potential of 3.37 V vs. Na/Na+. By employing a highly scalable synthesis procedure8 two types of NVP are prepared: pristine NVP and modified NVP by aliovalent doping. Sodium storage performances (specific capacity, rate performance and cycle life) of modified NVP outperforms the pristine NVP. The observed superior storage performance in modified NVP is attributed to enhanced activity of vanadium (V3+ to V4+ and V4+ to V5+)9 as confirmed by XPS studies and higher chemical diffusion coefficient. We also present storage performance, XPS studies, measurement of heat loss and internal resistance of 18650-type non-flammable NIB cells made using NVP (pristine- and modified- NVP) vs. HC with 1M NaBF4 in tetraglyme as electrolyte. The 18650 cell of pristine NVP vs. HC shows low energy density (47 Wh.kg− 1), moderate rate performance and poor cyclability. On the other hand, the 18650 cell of modified NVP vs. HC exhibits improved energy density (60 Wh.kg− 1) and enhanced rate and cyclic performances. Further, we report lesser heat generation in modified NVP vs. HC cell compared to pristine NVP vs. HC cell. Corresponding internal resistance of these 18650 cells measured at different depths of discharge (DoD) and temperature intervals reveal improved chemical diffusion coefficient, and substantial reduction in charge transfer resistance of the modified NVP vs. HC cell caused by aliovalent doping of NVP. The work presented here for introducing a safe NIB technology for stationary storage application is an illustration of R&D with a long value chain: scale-up production of cathode materials, commercial type cell fabrication, investigation of storage performance, estimation of heat generation, quantification of heat loss in terms of internal resistance. This translational R&D at NUS thus bridges academics and industries.

Online Internal Resistance Measurement Application in Lithium Ion Battery Capacity and State of Charge Estimation

State of charge (SOC) and state of health (SOH) are two significant state parameters for the lithium ion batteries (LiBs). In obtaining these states, the capacity of the battery is an indispensable parameter that is hard to detect directly online. However, there is a strong correlation relationship between this parameter and battery internal resistance. This article first shows a simple and effective online internal resistance detection method. Secondly, the relationship between the measured internal resistance and the LiBs capacity is established by linear fitting. Finally, the capacity through internal resistance conversion is applied in SOC estimation. The estimation results show that this method can effectively enhance the SOC estimation accuracy regardless of temperature change and battery degradation.

Online Lithium-Ion Battery Internal Resistance Measurement Application in State-of-Charge Estimation Using the Extended Kalman Filter

The lithium-ion battery is a viable power source for hybrid electric vehicles (HEVs) and, more recently, electric vehicles (EVs). Its performance, especially in terms of state of charge (SOC), plays a significant role in the energy management of these vehicles. The extended Kalman filter (EKF) is widely used to estimate online SOC as an efficient estimation algorithm. However, conventional EKF algorithms cannot accurately estimate the difference between individual batteries, which should not be ignored. However, the internal resistance of a battery can represent this difference. Therefore, this work proposes using an EKF with internal resistance measurement based on the conventional algorithm. Lithium-ion battery real-time resistances can help the Kalman filter overcome defects from simplistic battery models. In addition, experimental results show that it is useful to introduce online internal resistance to the estimation of SOC.