Constant Current Discharge Test Research Articles

A novel vanadium-copper rechargeable battery for solar energy conversion and storage

To enhance the utilization of abundant yet intermittent sunlight, the integration of solar energy conversion and storage has received increasing attention, and utilizing photoelectrodes to drive non-spontaneous reversible redox reactions provides a promising solution. This study proposes a triple-compartment system combining dual-photoelectrode (TiO2 and pTTh) with vanadium-copper electrolytes for integrated solar energy conversion and storage. The system can convert solar energy into chemical energy under simulated solar illumination (100 mW∙cm−2, AM 1.5G) and controllably release the stored chemical energy in the form of electrical energy. The system achieves a discharge open-circuit voltage of 0.47 V and a short-circuit current density of 1.3 mA∙cm−2. In constant current discharge tests, a discharge capacity of 2 mAh is observed at 0.3 mA∙cm−2.

Dual photoelectrode-drived Fe–Br rechargeable flow battery for solar energy conversion and storage: A cost-effective approach

The integrated design of solar energy conversion and storage systems has attracted increasing attention, and non-spontaneous redox reactions driven by dual photoelectrodes provide a potential solution to this issue. This study presents a solar rechargeable flow battery (SRFB) that combines dual photoelectrodes (BiVO4 or Mo–BiVO4 as photoanode, polyterthiophene (pTTh) as photocathode) with cost-effective redox pairs (Fe3+/Fe2+ and Br3−/Br−). The system charges under simulated solar illumination (100 mW∙cm−2, AM 1.5G) and releases stored energy controllably as electrical energy. Research indicates the Mo–BiVO4 photoanode and pTTh photocathode achieve an open-circuit voltage of 0.34 V and a short-circuit current density of 0.38 mA cm−2. Using a specially designed Fe3+/Fe2+-Br3−/Br− (Fe–Br) SRFB device made via 3D printing, a charging photocurrent of approximately 1.9 mA cm−2 is attained. In constant current discharge tests, an initial discharge voltage of 0.23 V is observed at 0.1 mA∙cm−2 within the 10 discharge cycles, demonstrating system stability and offering a viable solution for low-cost, large-scale solar energy storage and conversion.

Effects of flocculant and corrosion inhibitor compounding on the electrochemical corrosion behavior of the anode in Al-air batteries

To solve the problem of precipitates affecting battery performance in aluminum-air batteries. This study employed a variety of techniques—including flocculant-simulated sedimentation experiments, electrochemical assays, constant current discharge tests, and microscopic morphology assessments—to evaluate the synergistic effects of corrosion inhibitors and flocculants in the electrolyte of aluminum-air batteries. The inorganic polymer compound polyalumi rlillm sulfate (PSA) and the inorganic compound aluminum sulfate were investigated in a 4 mol/L NaOH+ 0.06 mol/L Na2SnO3 solution to elucidate the electrochemical corrosion mechanism of the 5052 aluminum alloy anode, as well as the sedimentation time and effect of colloidal precipitation. The results showed that the compounding of the two flocculants with the conventional corrosion inhibitor Na2SnO3 enhanced both the sedimentation rate of aluminum hydroxide in alkaline media and decreased the corrosion rate of the aluminum anode. Specifically, 3 g/L PSA was found to be most efficacious, elevating the sedimentation efficiency by 70.6%. Additionally, 1 g/L PSA demonstrated the most significant inhibitory effect on the self-corrosion of 5052 aluminum alloy, leading to an increase in the anode battery's capacity density by 15.5–35.1%. The synergistic action of flocculants and corrosion inhibitors chiefly accelerated the sedimentation rate of precipitates, maintained electrolyte conductivity, and facilitated the formation of a protective film on the surface of the aluminum anode to reduce the self-corrosion rate of aluminum, thereby promoting the improvement of discharge performance of aluminum-air batteries.

New Parameter Identification Method for Supercapacitor Model

The paper introduces a straightforward procedure for estimating the electrical parameters of a simple, but reasonably accurate, two-branches model of a supercapacitor (SC). The equivalent electrical circuit model includes the voltage and frequency dependence on the SC’s capacitance, neglecting the self-discharge phenomenon, so it is mainly devoted to short and mid-term simulations suitable for most industrial applications. The estimation procedure of the electrical parameters starts by analysing the experimental data achieved by a common constant-current discharge test. Such data are used to build a fitting function which is compared with the analytical solution and numerical approximations for the SC’s voltage evolution. Thus, initial estimated values of the electrical parameters are obtained through simple relations and are optimised by implementing the least squares method. The procedure is validated after an easy and fast extraction of the optimal parameters of the two-branches model of an SC. Several tests involving a commercial SC have been carried out in Simulink and the results have been compared against experimental data. A good accuracy of the two-branches model in a wide range of constant-current charging/discharging cycles is reported.

Influence of Aviation Conditions on Lithium-Ion Batteries

Stopping climate change and global temperature rise needs a determined course of action in several technology fields and the development of ZERO-CO2 aircrafts and low emission battery-ICE aircrafts, as well. Batteries in hybrid-electric or fully-electric aircrafts are an option to decrease emissions. The battery requirements for the aviation sector regarding specific energy, energy density and safety are high. Lithium-ion batteries are today the only commercially available technology to meet these requirements, but adequate technology readiness is only proven for the automobile sector while TRL levels 8 and 9 for implementation readiness of batteries in the aviation sector is still ongoing. A crucial aspect for aviation applications is the operation behavior in high altitude including low temperature, wide humidity ranges and especially low pressure. There is little published information available on the effects of low pressure on battery performance. Therefore, different commercially available lithium-ion batteries were tested from atmospheric pressure down to 250 hPa, which corresponds to a flight altitude up to 10,000 m, according to the International Standard Atmosphere (ISA). Since NMC and NCA cathode materials are promising for aviation due to their high specific energy, and LFP cells are promising because of their high safety, the following batteries were selected: 20 Ah HP602030 LFP cylindrical cell (EAS Batteries GmbH, GER). 10 Ah HE 341440 NCA cylindrical cell (EAS Batteries GmbH, GER). 12 Ah SLPB065070180 NMC pouch cell (Kokam Co. Ltd., KOR) To examine the influence of pressure on the battery behavior, constant current discharge tests at 1C 0.5C and 2C rates as well as impedance measurements in 10% SOC steps were performed in a climate controlled low-pressure chamber. The batteries were operated under different temperatures and in controlled low pressure. The pressure was first set to atmospheric pressure as a reference and then lowered to 750 hPa, 500 hPa and 250 hPa. To further examine altitude influences, current cycles and impedance spectroscopy were performed at different temperature and humidity values.The behavior of the cylindrical cells showed hardly any pressure dependency, while the examined pouch cell’s behavior did show a pressure dependency.All batteries showed strong temperature dependency but hardly any humidity dependency.In this presentation the influence of pressure, temperature and humidity on voltage, capacity, resistance and impedance of the afore mentioned batteries will be discussed. The batteries are compared regarding their aviation applicability with special respect to low pressure. The parameters for each environmental condition can then be used to parameterize a battery model suitable for aviation applications.

Lithium-ion battery state-of-charge estimation based on a dual extended Kalman filter and BPNN correction

It is challenging for a battery management system to estimate the State-Of-Charge (SOC) of batteries. A novel model-based method, using a Dual Extended Kalman Filtering algorithm (DEKF) and Back Propagation Neural Network (BPNN), is proposed to estimate and correct lithium-ion batteries. The results of acceptable SOC estimation are achieved using the DEKF to estimate the battery SOC and simultaneously update model parameters online, while the SOC estimation error is in real-time predicted by the trained BPNN. To further reduce the SOC estimation error, the SOC estimated by the DEKF is corrected by adding the predicted estimation error. The SOC estimation results between the original DEKF and BPNN-based updated DEKF methods under the Federal Urban Driving Schedule (FUDS), the Dynamic Stress Test (DST), the Beijing Dynamic Stress Test (BJDST) and the US06 Highway Driving Schedule are compared. Experimental results show that the SOC error reduces considerably after correcting the estimated SOC. The corrected SOC Root-Mean Square Errors (RMSEs) decrease by an average of seven times compared with the case of no correction. The constant current discharge test verifies the generality and robustness of the proposed method. The modification to the SOC estimation results using ordinary EKF under the above four sophisticated dynamic tests verifies the effectiveness of the proposed method.

Computationally Efficient State-of-Charge Estimation in Li-Ion Batteries Using Enhanced Dual-Kalman Filter

This paper proposes a state-of-charge estimation technique to meet highly dynamic power requirements in electric vehicles. When the power going in/out the battery is highly dynamic, the statistics of the measurement noise are expected to deviate and maybe change over time from the expected laboratory specified values. Therefore, we propose to integrate adaptive noise identification with the dual-Kalman filter to obtain a robust and computationally-efficient estimation. The proposed technique is verified at the pack and cell levels using a 3.6 V lithium-ion battery cell and a 12.8 V lithium-ion battery pack. Standardized electric vehicle tests are conducted and used to validate the proposed technique, such as dynamic stress test, urban dynamometer driving schedule, and constant-current discharge tests at different temperatures. Results demonstrate a sustained improvement in the estimation accuracy and a high robustness due to immunity to changes in the statistics of the process and measurement noise sequences using the proposed technique.

Innovative battery thermal management system based on hydrogen storage in metal hydrides for fuel cell hybrid electric vehicles

This study proposes a new approach for dealing with the thermal management of batteries in fuel cell hybrid electric vehicles, by introducing a new concept of on-board energy storage system which integrates the battery pack with a metal hydride tank. The rationale behind this solution is to use the exothermic absorption and endothermic desorption processes of hydrogen in metal hydrides for heating and cooling the battery pack, respectively, thus ensuring an optimal thermal management control. An experimental investigation is carried out on a prototype in order to proof the concept and preliminary assess its feasibility for actual implementations. The results show that the system is capable to effectively control the temperature variations within the battery pack: for 1C and 1.5C constant-current discharge tests, a desorption of 30%–40% of hydrogen, over the total amount stored into the metal hydride tank of the system, allows the final average temperature of the battery pack to be around 15 °C lower than the one reached without thermal management. Moreover, it is found that the system is potentially capable of providing a suitable thermal management for more than four hours under realistic driving conditions. The proposed energy storage system also achieves inherently high gravimetric and volumetric energy densities, with theoretical values equal to 182 Wh/kg and 530 Wh/L, respectively. These estimates represent reference values for further design improvements.

A Comparative Study on the Parameter Identification of an Equivalent Circuit Model for an Li-ion Battery Based on Different Discharge Tests

An effective model of battery performance is important for battery management systems to control the state of battery and cell balancing. The second-order equivalent circuit model of a lithium-ion battery is studied in the present paper. The identification methods that include the multiple linear regression (MLR), exponential curve fitting (ECF) and Simulink design optimization tool (SDOT), were used to determine the model parameters. The aim of this paper is to compare the validity of the three proposed algorithms, which vary in complexity. The open circuit voltage was measured based on the pulse discharge test. The voltage response was collected for every 10% SOC in the interval between 0–100% SOC. The battery voltages calculated from the estimated parameters under the constant current discharge test and dynamic discharge tests for electric vehicles (ISO and WLTP) were compared to the experimental data. The mean absolute error and root mean square error were calculated to analyze the accuracy of the three proposed estimators. Overall, SDOT provides the best fit with high accuracy, but requires a heavy computation burden. The accuracy of the three methods under the constant current discharge test is high compared to other experiments, due to the nonlinear behavior at a low SOC. For the ISO and WLTP dynamic tests, the errors of MLR are close to that of SDOT, but have less computing time. Therefore, MLR is probably more suitable for EV use than SDOT.

Operation of liquid e-fuel cells using air as oxidant

The promising features and capabilities of liquid fuel cells for power generation and further application in electric vehicles have drawn more research attention in recent times. Notably is the recently proposed and demonstrated fuel cell which employs an electrically rechargeable liquid fuel (e-fuel) along with a catalyst-free material at its anode. The smooth and successful functioning of the e-fuel cell generally requires the supply of oxidant at its cathode. However, the space and storage requirement with the use of pure oxygen as oxidant not only limits the energy density of the fuel cell, but as well results in higher cost. Herein, the operation and performance of this e-fuel cell is examined with the use of air as oxidant, in lieu of the commonly used pure oxygen, at the cell cathode. A peak power density of 168.3 mW cm−2 was obtained when the cathode is fed with air. Such performance when air is employed as oxidant in the e-fuel cell outperforms most conventional direct liquid fuel cells that are even fed with oxygen and thereby demonstrates the use of air as a promising alternative for future application. The performance of the cell when operated with air at various flow rates and operating temperatures, and during a constant current discharge test were also examined. This study therefore provides basis and useful insights for future investigations towards utilizing and catalyzing air as oxidant in the e-fuel cell for improved cell performance.

Modeling and Validation of the Impact of Electric Current and Ambient Temperature on the Thermoelectric Performance of Lithium‐Ion Batteries

A wider electric vehicle penetration strategy demands an improvement in charging time, performance, battery life, and safety, which can be achieved through battery temperature control. A collective impact of load and ambient on the battery needs assessment for thermal management system optimization. Herein, a multiscale multidomain numerical model is utilized on ANSYS Fluent platform. Galvanostatic and constant current discharge tests are conducted for battery modelling and validation. The first of three aspects considered is the cyclic relationship between the thermal parameters. Low ambient temperature of 0 °C at 1 C discharge rate increases the heat generation rate to 50 kW m−3 which then dips to 40 kW m−3 due to rise in battery temperature. The second is the inter‐relationship among the thermal and the electrical parameters. A faster rise in battery temperature at low ambient temperature causes an elevation in the voltage and hence the electrical performance. The third is the collective impact of thermal and electrical parameters. At 0 °C ambient temperature, an increase in discharge rate from 1 to 1.5 C increases the battery capacity by at least 6%. With the establishment of the predictive performance model of the battery, this study is expected to provide a guideline for optimizing the thermal management systems.

The effects of cell configuration and scaling factors on constant current discharge and dynamic charge acceptance in lead-acid batteries

The active materials of batteries are often tested and selected at the cell level, which prevents comparability to battery-level performance. In the case of a typical lead-acid battery used in a vehicle, the performance after a few months in operation is not necessarily the same as it was during cell-level tests. The goal of this manuscript is to outline the most common reasons for the divergence in test results between cell-level tests and commercial batteries with respect to dynamic charge acceptance (DCA). To do so, this study tested 12 V-70 Ah enhanced flooded batteries (EFB) for their DCA properties. Afterwards, these batteries were dissembled to extract three 2 V test cells, some with a lower number of plates (3P2N and 2P1N). The aim of this investigation was to determine how the DCA of the original battery was affected by changing the plate count and the ratio between the positive active mass, the negative active mass, and the electrolyte by using industrially manufactured cell components – rather than introducing sources of errors by using handmade cells. Both the test batteries and the test cells were subjected to two different constant current discharge tests: the reserve capacity (RC) test and the C20 test. The DCA test according to Japanese Standard SBA S0101 2014 was also conducted. It was particularly important to identify operational conditions and scaling factors (e.g. voltages, currents, and acid densities) on the cell level – for cells with and without lower plate counts. Currently, these are only defined for battery testing according to standard test procedures. Our test cell design, with a reduced, asymmetric set of plates, generated an acid surplus and a PAM surplus, which in turn had major effects on steady-state properties such as the constant current discharge (as the RC test and C20 test showed). DCA battery and cell-level results are not comparable in terms of absolute values, especially for cells with lower plate count. The DCA results for single cells are systematically better for a lower plate count, which may be attributed to excess acid volume.

Equivalent circuit modeling of sodium-ion batteries

Accurate modeling of sodium-ion batteries (SIBs) plays a vital role in the optimal development of the battery management system (BMS). In this study, the equivalent circuit models (ECMs) with different resistance-capacitance (RC) numbers are thoroughly investigated. The relationship between circuit parameters and state of charge (SOC) is modeled as polynomial functions. The Bayesian information criterion is used to assist in optimal model selection by balancing the trade-off between model accuracy and model complexity. Two typical types of operation conditions, i.e. hybrid pulse power characterization/dynamic stress tests and constant current discharge tests, are conducted to evaluate the model performance. Both fitting and prediction results demonstrate that the ECMs with three-RC network can describe the terminal voltage response of a 1 Ah pouch-type SIB. The accurate modeling strategy provides a promising tool to state monitoring and control in BMS.

A comparative study of equivalent circuit models for a Li-ion battery pack of an electric Tuk-Tuk

This paper presents developments and validations of Lithium Nickel Manganese Cobalt Oxide (NMC) battery cell and battery pack models. A 7.4 kWh NMC battery pack is installed on an electric Tuk-Tuk equipped with a 3 kW motor. The battery pack is configured of four cells connected in parallel and 20 sets of the four cells connected in series. Based on the first-order and the second-order equivalent circuit models, battery cell and battery pack models are developed in Matlab/Simulink environment. For parameter identifications of the cell model, pulse discharge tests are performed at room temperature with 10% State of Charge (SOC) interval. The lumped heat capacitance method is applied to the battery models. The battery cell model is validated with SOC, cell center temperatures and terminal voltage using the experimental data of constant current discharge tests. With the battery pack configuration, the battery cell model is scaled up to match the battery pack voltage and its capacity. The dynamics of the battery pack models are validated with the vehicle testing data using the no-load, wide-open throttle and real road tests. The simulation results show good agreement with the test data. Using the developed battery models, vehicle performance and its energy consumption can be improved by optimizing battery cell and pack configurations.

Preparation of tungsten-based material and the effect on oxygen reduction reaction

Different Tungsten bronze powders were prepared from W powder, WO3 and alkali carbonate by high temperature synthesis method, then were doped into spent battery powders to obtain an oxygen reduction catalyst with low cost and excellent catalytic ability. According to the XRD and SEM of the powders and the electrochemical analysis of the powders after the preparation of the electrodes, there were a large number of oxygen vacancies in Rb0.27WO3 crystal and a four-electron transfer process in the process of dissolved oxygen, which were pivotal to improve the performance of oxygen reduction reaction catalyst. The cathode of metal-air battery doped with Rb0.27WO3 had the highest voltage in the constant-current discharge test platform, and the platform voltage showed the most stable performance under different current densities, especially under the high current densities.

A Variational Bayesian and Huber-Based Robust Square Root Cubature Kalman Filter for Lithium-Ion Battery State of Charge Estimation

An accurate state of charge (SOC) estimation is vital for safe operation and efficient management of lithium-ion batteries. To improve the accuracy and robustness, an adaptive and robust square root cubature Kalman filter based on variational Bayesian approximation and Huber’s M-estimation (VB-HASRCKF) is proposed. The variational Bayesian (VB) approximation is used to improve the adaptivity by simultaneously estimating the measurement noise covariance and the SOC, while Huber’s M-estimation is employed to enhance the robustness with respect to the outliers in current and voltage measurements caused by adverse operating conditions. A constant-current discharge test and an urban dynamometer driving schedule (UDDS) test are performed to verify the effectiveness and superiority of the proposed algorithm by comparison with the square root cubature Kalman filter (SRCKF), the VB-based SRCKF, and the Huber-based SRCKF. The experimental results show that the proposed VB-HASRCKF algorithm outperforms the other three filters in terms of SOC estimation accuracy and robustness, with a little higher computation complexity.

Adaptive Dual Extended Kalman Filter Based on Variational Bayesian Approximation for Joint Estimation of Lithium-Ion Battery State of Charge and Model Parameters

An accurate state of charge (SOC) estimation is vital for the safe operation and efficient management of lithium-ion batteries. At present, the extended Kalman filter (EKF) can accurately estimate the SOC under the condition of a precise battery model and deterministic noise statistics. However, in practical applications, the battery characteristics change with different operating conditions and the measurement noise statistics may vary with time, resulting in nonoptimal and even unreliable estimation of SOC by EKF. To improve the SOC estimation accuracy under uncertain measurement noise statistics, a variational Bayesian approximation-based adaptive dual extended Kalman filter (VB-ADEKF) is proposed in this paper. The variational Bayesian inference is integrated with the dual EKF (DEKF) to jointly estimate the lithium-ion battery parameters and SOC. Meanwhile, the measurement noise variances are simultaneously estimated in the SOC estimation process to compensate for the model uncertainties, so that the adaptability of the proposed algorithm to dynamic changes in battery characteristics is greatly improved. A constant current discharge test, a pulse current discharge test, and an urban dynamometer driving schedule (UDDS) test are performed to verify the effectiveness and superiority of the proposed algorithm by comparison with the DEKF algorithm. The experimental results show that the proposed VB-ADEKF algorithm outperforms the traditional DEKF algorithm in terms of SOC estimation accuracy, convergence rate, and robustness.

Effect by adding Ce and In to Mg–6Al Alloy as anode on performance of Mg-air batteries

In order to improve discharge activity and utilization of anode material for Mg-air batteries, four anode materials are prepared. The electrochemical performances of these anodes are evaluated by electrochemical impedance spectroscopy and polarization curves. The discharge performances of Mg-air batteries are studied by a constant current discharge test. The results show that the discharge activity of magnesium alloy is improved remarkably with the addition of indium. The corrosion potentials of Mg–6Al–1In and Mg–6Al–1In–1Ce" can reach −1.573 V and −1.600 V respectively. The addition of cerium can reduce the rate of self-corrosion of anode. The corrosion current is only 2.196 × 10−6 mA·cm−2. The air batteries with Mg–6Al–1In as the anode have the highest discharge potential at applied current densities of 5, 10, 15 and 20 mA·cm−2. The anode utilization of an air battery with Mg–6Al–1In–1Ce as the anode can reach 48.5% at an applied current density of 20 mA · cm−2 for 300 min.

A New State of Charge Estimation Method for Lithium-Ion Battery Based on the Fractional Order Model

This paper presents that the fractional order Kalman filter (FOKF) method is used to estimate the state of charge (SOC) for lithium-ion battery based on the fractional order model. First, a fractional order battery model was established which can better reflect the dynamic characteristics of the battery. The fractional orders were identified by genetic algorithm. Then, compared with three other modeling methods in four aspects: maximum absolute error, maximum relative error, computational complexity and number of model parameters, it is shown that the fractional order model proposed in this paper is more accurate and reliable. The results shows that the maximum absolute error of the terminal voltage is 0.014 V under constant current discharge test. The accuracy improves 0.058 V comparing to the integer order model. Finally, the SOC was estimated through two methods. The results shows that the maximum absolute estimation error of SOC is under 0.02 by FOKF, which has higher accuracy and faster convergence speed compared with extend Kalman filter (EKF) method.

Integrated photocapacitors based on dye-sensitized TiO2/FTO as photoanode and MnO2 coated micro-array CNTs as supercapacitor counter electrode with TEABF4 electrolyte

Harvesting solar energy using dye-sensitized solar cells (DSSCs) has been a promising option. Successful integration of a DSSC electrode with an energy storage electrode represents the next challenge for the researchers. In this paper, the fabrication and characterization of an integrated dye-sensitized photoanode and a supercapacitor cathode or a photocapacitor has been presented. This novel device employs N-719 dye-sensitized titanium dioxide on fluorine-doped tin oxide glass substrate as the photoanode. The supercapacitive counter electrode comprises MnO2 coated, vertically aligned, micro-array patterned carbon nanotubes (MA-CNTs). The CNTs were grown on n++ silicon (Si) substrates in a hot filament chemical vapor deposition system followed by in-situ electrochemical deposition of MnO2. Tetraethyl ammonium tetrafluoroborate electrolyte was used to investigate the photovoltaic and energy storage performances of the photocapacitors under 1-sun illumination and constant-current discharge tests. A high discharge capacitance of 13 mF/cm2 at 0.932 V was achieved by coating MnO2 onto the high surface area of MA-CNTs due to the pseudocapacitive behavior of MnO2, which led to a nearly 3-fold increase in the short circuit current density to 0.749 mA/cm2 and more than a 2-fold enhancement in the open circuit voltage to 0.46 V, as compared to the baseline CNT counter electrode. The corresponding increase in the fill factor and efficiency was also observed. Overall, we have demonstrated the viability of a compact, easy to fabricate, integrated photocapacitor with promising energy generation/storage performance.