Battery Internal Resistance Research Articles

Effects of SiO2 Particle Size in Soggy‐Sand Electrolyte on Electrochemical Performance of Zinc‐Ion Batteries

AbstractThe presence of free water molecules in the aqueous electrolyte leads to serious side reactions at the interface, easy dissolution of the cathode material, and uncontrolled growth of zinc dendrites in Zn‐ion batteries, which hinders their practical applications. Here, we propose a type of SiO2‐based soggy‐sand electrolyte (ZnSO4+MnSO4 electrolyte with SiO2, SiO2‐ZMSO4) and focus on the effect of the SiO2 nanoparticle size on the performance of soggy‐sand electrolyte. It is found that SiO2 with smaller nanoparticle size provides higher porosity, and the SiO2 network‐formed can effectively trap the free water in the electrolyte, which increases the ionic conductivity of electrolyte, widens working voltage window, and decreases the internal resistance of batteries. As a result, the Zn//MnO2 batteries with 20 nm SiO2‐based soggy‐sand electrolyte show stable cycling performance and rate capacities. The specific capacity of the battery can be maintained at 198.5 mAh g−1 after 1200 cycles at 1 A g−1 without capacity degradation. The specific capacity can be increased by 100 mAh g−1 even at a high rate of 5 A g−1. This study provides the rule of particle selection for the development of aqueous soggy‐sand electrolytes used in aqueous rechargeable batteries.

Highly active nitrogen-phosphorus co-doped carbon fiber@graphite felt electrode for high-performance vanadium redox flow battery

Heteroatom-doped electrodes offer promising applications for enhancing the longevity and efficiency of vanadium redox flow battery (VRFB). Herein, we controllably synthesized N, P co-doped graphite fiber electrodes with conductive network structure by introducing protonic acid and combining electrodeposition and high temperature carbonization. H2SO4 and H3PO4 act as auxiliary and dopant, respectively. The synergistic effect between N and P introduces additional defect structures and active sites on the electrodes, thereby enhancing the reaction rate, as confirmed by density functional theory calculations. Furthermore, the conductive network structure of carbon fibers improves electrode-to-electrode connectivity and reduces internal battery resistance. The optimized integration of these strategies enhances VRFB performance significantly. Consequently, the N, P co-doped carbon fiber modified graphite felt electrodes demonstrate remarkably high energy efficiency at 200 mA cm−2, surpassing that of the blank battery by 7.9 %. This integrated approach to in-situ controllable synthesis provides innovative insights for developing high-performance, stable electrodes, thereby contributing to advancements in the field of energy storage.

Analysis on battery thermal management system based on flat heat pipe at high discharging rate

Power batteries are the core power source for electric vehicles. However, battery thermal management technology for electric vehicles will face more severe challenges in the future. Flat heat pipe has gradually received much attention in the field of battery thermal management due to its high heat conduction coefficient and lightweight structure. This paper focuses on the influence of flat heat pipe structural parameters on battery thermo-electrical performance by establishing simulation model of the battery cooling system, which makes contribution to the flat heat pipe structure design on optimizing battery overall performance. Based on the mechanism of working medium flow effect of flat heat pipe on the battery electrochemical heat generation, a coupled model of flat heat pipe-based battery system is established according to the relationship between battery electrochemical heat generation performance and flat heat pipe heat transfer characteristics. The accuracy of system model is further verified by experiment, and the battery thermo-electrical characteristics under different discharging conditions is simulated. The flat heat pipe-based battery thermal management system can effectively reduce the battery maximum temperature while improving the uniformity of battery temperature and state of charge (SOC). The reduction of the vapor chamber thickness causes the uneven distribution of vapor thermal resistance, so the battery maximum temperature and maximum temperature difference will become larger, which will further cause the uneven distribution of battery internal resistance, and this will finally increase the non-uniformity of battery module discharging current distribution. A structural design method of the flat heat pipe-based battery thermal management system is developed with the battery thermo-electrical coupling performance as the design objective and the flat heat pipe structural parameters (total thickness, vapor chamber thickness, total length) as the optimization variables. Compared with the original scheme, the battery maximum temperature can be reduced by 6.4% under transient high-rate discharging conditions with the modified flat heat pipe based on the proposed design method, while the battery maximum temperature and SOC difference can also be reduced by 18.4% and 16.3%, respectively.

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.

Research on the Performance Improvement Method for Lithium-Ion Battery in High-Power Application Scenarios

With the development of technology, high-power lithium-ion batteries are increasingly moving towards high-speed discharge, long-term continuous output, instantaneous high-rate discharge, and miniaturization, and are being gradually developed towards the fields of electric tools, port machinery and robotics. Improving the power performance of batteries can be achieved from multiple dimensions, such as electrochemical systems and battery design. In order to improve the power performance of lithium-ion batteries, this paper proposes design methods from the perspective of electrochemical systems, which include increasing the high-rate discharge capacity and low impedance of the battery. This article also studies the preparation of high-power lithium-ion batteries. This article aims to improve the rate performance of batteries by studying high-performance cathode materials, excellent conductive networks, and high-performance electrolytes. This article successfully screened high-performance cathode materials by comparing the effects of different particle sizes of cathode materials on electrode conductivity and battery internal resistance. By comparing the effects of electrolyte additives under pulse cycling, high-quality electrolyte additive materials were selected. By comparing the effects of different types, contents, and ratios of conductive agents on electrode conductivity, battery internal resistance, high-quality conductive agents, and appropriate ratios were selected. Finally, a 10 Ah cylindrical high-power lithium-ion battery with a specific energy of 110 Wh/kg, pulse discharge specific power of 11.3 kW/kg, an AC internal resistance of ≤0.7 m Ω, a 10C full capacity discharge cycle of over 1700, a 30C full capacity discharge cycle of over 500, and a continuous discharge capacity of 10C–30C, and a pulse discharge capacity of over 100C was prepared.

Battery parameter identification method of a battery module based on a multi-physical measurement system

The secondary utilization of retired electric vehicle batteries is beneficial for improving resource utilization efficiency. Capacity and internal resistance are battery parameters that can reflect the battery state. To identify the parameters of a single battery in a battery module, it is usually necessary to disassemble the battery module. The process is complex, time-consuming, and unsafe. In this paper, a battery parameter identification method without disassembling the battery module is developed based on a multi-physical measurement system. First, a multi-physical electrical-thermal-spatial measurement system is constructed to measure the physical parameters of the battery module during charging and discharging. Then, the electrical model and the thermal model are developed. To obtain the capacity and internal resistance of each cell within the battery module, a battery parameter identification model is established with temperature and total battery current as input parameters and battery capacity and internal resistance as output parameters. Batteries with different capacities and internal resistances are connected in series and parallel to simulate retired battery modules for electric vehicles. The battery parameters are identified using the method presented in this paper. According to the experiments, the relative errors of parameter identification for battery capacity and internal resistance are both within 9 %. This method can improve the efficiency of the battery screening process as well as the reliability of the battery system.

Electrical Conductivity Measurements of the Binary NaCl-CaCl2, the Ternary NaCl-CaCl2-BaCl2 and the Quaternary NaCl-CaCl2-BaCl2-ZnCl2 Molten Salts

An emerging set of batteries, called the molten salts or all liquid battery, are designed for cheap energy storage and electrical grid buffering purposes (1). Some molten salt batteries are commercial or close to commercial like the ZEBRA, NaS and Ambri batteries, however, most of these battery technologies are still on an experimental, lower TRL level but can become increasingly important in the future as the shift towards more intermittent energy sources emerge and as the development of these batteries become more mature. One suggested battery technology is the Na-Zn battery (2). This battery technology is currently further investigated in the EU funded SOLSTICE project (Grant Agreement No 963599). The Na-Zn battery will have Na and Zn electrodes and the electrolyte – the molten salt – will be a NaCl-CaCl2 based electrolyte, with additions of BaCl2 or perhaps even BaCl2 and SrCl2. The NaCl content of the electrolyte gives the charge of the battery, CaCl2 lowers the operating temperature and BaCl2 and SrCl2 increases the density of the electrolyte. The operating temperature of the battery is approximately 600 °C and joule heat generated inside battery during charging and discharging due to resistance of the electrolyte allows to maintain this operating temperature. The composition of electrolyte changes with the battery state of charge hence the internal resistance of battery is not constant during normal operation. Therefore, precise data of electrical conductivity of the electrolyte is required for modelling its performance thermal balance.A method for measuring electrical conductivity has been built in the SINTEF laboratory. The setup used for the measurements is presented in Figure 1a. It consists of two tungsten electrodes immersed in molten electrolyte – one electrode is stationary and the other is moving inside a capillary. Position of the moving electrode inside the capillary is precisely controlled by a height gauge. Shielded thermocouple is used for measuring temperature. To avoid polarization of electrodes during measurement, electrical impedance spectroscopy (EIS) at open circuit potential is used. The principle of the method is that resistance between the electrodes is measured at different positions of the moving electrode inside the capillary. Measured resistance can be expressed by the following formula: R=R0+ρ·(l/A) Where R0 is the offset resistance of electrolyte outside capillary including resistance of electrodes and leads,ρ is the resistivity of electrolyte, l is the length between end of capillary and tip of the moving electrode, A is the area of the capillary. The measurement of resistance is repeated at different positions of the moving electrode relative to the chosen reference position. Since R0 and A are constant, resistivity can be calculated knowing only the tangent of function R = f(l) (Figure 1b) divided by A. The presented approach is characterized by high precision and robustness due to no requirement of cell constant values, which is problematic to estimate at high temperature. It is only based on relative movement of one electrode which is easy to control. In addition, a higher number of positions of the moving electrode at which the measurement is performed effectively helps to eliminate errors. Conductivity is the inverse resistivity. Electrical conductivity measurements were done at a range of temperatures, from 600 °C to 800 °C with 50 °C steps and the results are presented in the form of linear formulas intended for use in User Defined Functions in modelling.Conductivity of various chloride salt compositions containing NaCl, CaCl2, BaCl2 and ZnCl2 have been investigated using the presented technique. It is generally found that the electrical conductivity is almost linear with temperature increase in the range of liquidus temperature up to approximately 800 °C for the investigated electrolyte compositions. Above that region the relationship is not linear anymore. This region is not presented in this presentation. It is also found that the conductivity increases with increasing NaCl content and that larger cations like Ca and Ba reduce the conductivity of the molten salt. The method has proven very powerful to measure electrical conductivity on molten salts and the results are comparable to experimental results found in literature (3).

Research on rapid extraction of internal resistance of lithium battery based on short-time transient response

Unlike laboratory measurements and online parameter observations based on long-term continuous operation data, offline fast measurement of battery parameters is widely used for convenient and accurate acquisition of battery parameters in battery production and maintenance processes. However, too short allowable measurement time in engineering results in a small amount of dynamic information that the algorithm can obtain and unclear initial state values, making it difficult to improve the accuracy of the algorithm. This paper employs a local coordinate system established in the vicinity of the measurement moment to extract the transient behavior of battery terminal voltage response under excitation current, and investigates the characterization capability of these transients on ohmic and polarization internal resistance of batteries at different time points. Moreover, based on an equivalent circuit model, it evaluates how initial values of transient voltage affect accuracy in calculating internal resistance. Through customized working condition verification, the selection principles for rapid identification of time points and the basic requirements for excitation conditions have been determined. Comparative verification of online parameter identification results based on continuous time series demonstrates that the fast identification algorithm can accurately identify Ohmic internal resistance and effectively characterize the variation law of battery polarization.

Analysis of fuel economy reduction factors of hybrid electric vehicles in winter using on-road driving data

The reduction in driving range during winter is one of the major disadvantages of battery electric vehicles and hybrid electric vehicles. On-road driving tests showed that the fuel efficiency was 23.1 km/L at an ambient temperature of 20 °C, but it dropped to 20 km/L at 0 °C under the same driving conditions. Therefore, this study analyzed the effect of road load and battery internal resistance on fuel economy reduction during winter. The road load and battery internal resistance for various temperatures were extracted from on-road driving data using intuitive and simple methods. The results showed that the road load was the major factor that reduced the fuel economy of hybrid electric vehicles in winter, whereas the effect of battery internal resistance on fuel economy reduction was negligible. As the ambient temperature decreased from 20 °C to 0 °C, the energy loss due to road load increased by 2.1 kWh, while the energy loss due to battery internal resistance only increased by 0.0345 kWh. Although this study focused on hybrid vehicles, the methodology used can also be applied to battery electric vehicles.

Insights into mechanics and electrochemistry evolution of SiO/graphite anode by a composite electrode model

Silicon-based materials are crucial for high-capacity anodes, but their volume expansion in batteries due to the presence of silicon requires further analysis and research. Silicon monoxide/Graphite (SiO/C) is a composite material that combines the volume expansion of silicon oxide material with the practical application of carbon material. Therefore, understanding its behavior during actual use is important, particularly in full batteries and in pairs with high-capacity LiNi0.8Co0.15Al0.05O2 (NCA) cathode. There are fewer studies on this topic, which highlights the need for research. Thus, in this work, SiO/C composite negative electrodes are prepared with different compaction densities (CDs) of 1.38, 1.52, and 1.62 g cm−3. Pouch cells are assembled with NCA positive electrode to investigate the changes in battery thickness and internal resistance under different CDs and state of charge (SOC), as well as the Coulombic efficiency and cyclic performance of batteries are also examined. Additionally, the capacity-voltage curves, expansion curves under different CDs and SOC, particle stress change, and lithium concentration distribution under different CDs are comprehensively simulated. Thus, the evolution of lithium concentration distribution and electrodes volumetric strain during charge and discharge are directly presented. The established model through matching experimental data provides a research basis for predicting the performance of SiO/C negative electrodes, especially its electrochemical and mechanical performance evolution in high‑nickel full batteries. This study has important implications for the development of high-performance silicon-based anodes in practical applications.

Tailoring the discharge performance of extruded Mg-Sm-Al anode for Mg-air battery applications via control of Al content

We investigated the discharge performance and electrochemical properties of an as-extruded Mg-5Sm-xAl (x = 0,1,3) anode for Mg-air batteries. Adding Al modified the phase composition and grain size of the anode. The addition of 1 wt% Al (Mg-5Sm-1Al) induced a high discharge voltage and power density due to the stimulation of the evenly distributed, fine Al11Sm3 particles. However, these particles increased the parasitical anodic hydrogen reaction rate, resulting in a decrease in anodic efficiency. These properties make the anode suitable for high-power density applications. The addition of 3 wt % Al (Mg-5Sm-3Al) promoted the formation of an aluminium oxide film on the anode surface, which suppressed the anodic hydrogen reaction to improve the anodic efficiency. This film increased the battery's internal resistance resulting in low voltage. This anode is a good candidate for heavy-duty battery applications, where a steady voltage output and long service life are desired. By controlling the Al content, the tailoring of discharge performance of the Mg-Sm-Al anode is feasible to satisfy different battery load requirements.

Electric Aircraft Battery Performance: Examining Full Discharge Under Two Conditions

The understanding of battery performance, particularly over the full course of discharge and over battery life is critical to allow pilots to maintain safety in electric aviation. In this study, an electric aircraft powered by two Lithium-Ion battery packs is used as a test article. The objectives of the current study are to build on previous work by conducting two full tests discharging both battery packs from a 100% charge. This allows examination of the battery performance a) under a constant power output and b) with periodic tests of the maximum power available. In addition to state of charge (SOC), remaining flight time, battery temperature, and motor power, this study presents data on motor RPM, torque, voltage, current, battery internal resistance, and available energy. The data on motor power indicates that the available maximum power decreases with lower SOCs when the throttle settings are varied; however, at lower power settings, such as an optimum cruise at 27 kW, the motor power remains constant and as expected during discharge. Also, the constant power setting illustrates that there are inflection points in physical battery characteristics. These results confirm that electric aircraft performance changes during a flight are different than what a pilot expects from a gasoline-powered aircraft. The longer the aircraft flies at different throttle settings, the faster the batteries discharge; the discharge curve is nonlinear. Thus, a piston-trained pilot’s expectation for an aircraft’s performance later in a flight will not match an electric aircraft.

Battery loss prediction using various loss models: A case study for a residential building

This work compares and quantifies the annual losses for three battery system loss representations in a case study for a residential building with solar photovoltaic (PV). Two loss representations consider the varying operating conditions and use the measured performance of battery power electronic converters (PECs) but differ in using either a constant or current-dependent internal battery cell resistance. The third representation is load-independent and uses a (fixed) round trip efficiency. The work uses sub-hourly measurements of the load and PV profiles and includes the results from varying PV and battery size combinations. The results reveal an inadequacy of using a constant battery internal resistance and quantify the annual loss discrepancy to −38.6%, compared to a case with current-dependent internal resistance. The results also show the flaw of modelling the battery system’s efficiency with a fixed round trip efficiency, with loss discrepancy variation between −5 to 17% depending on the scenario. Furthermore, the necessity of accounting for the cell’s loss is highlighted, and its dependence on converter loading is quantified.

Effect of Binder on Internal Resistance and Performance of Lithium Iron Phosphate Batteries

In this paper, a water-based binder was prepared by blending polyacrylic acid (PAA) and polyvinyl alcohol (PVA). The effects of the binder on the internal resistance and electrochemical performance of lithium iron phosphate batteries were analyzed by comparing it with LA133 water binder and PVDF (polyvinylidene fluoride). First, positive electrode sheets were prepared by using PVDF, PAA/PVA and LA133 as binders, respectively. and the effects of binders on the resistivity and compaction density of electrode sheets were analyzed. Secondly, the buckle battery and the 14500 steel shell full battery were prepared by using PVDF, PAA/PVA and LA133 as binders, respectively. The influence of the positive electrode materials prepared by different binders on the internal resistance of the battery and on the charge and discharge performance and cycle performance of the battery was analyzed. The results show that the internal resistance test of 14500 type whole cell prepared with PVDF, PAA/PVA and LA133 as the binder shows that the internal resistance of sample batteries LFP-F, LFP-AV and LFP-L are 40.5 mΩ, 33.2 mΩ and 35.7 mΩ, respectively. The internal resistance of the battery prepared by self-made PAA/PVA binder is the lowest.

A data-driven approach for estimating state-of-health of lithium-ion batteries considering internal resistance

State-of-health (SOH) estimation of lithium-ion batteries is an important issue in electric vehicle energy management. The complication of the internal electrochemical reaction mechanism and the uncertainty of the external operating conditions pose a significant challenge to SOH estimation. This paper develops a data-driven approach to estimate the SOH of lithium-ion batteries with consideration of the battery's internal resistance, which is used as a bridge to effectively integrate the equivalent circuit model (ECM) and the data-driven method. We try to identify the internal resistance under constant current charging conditions by simplifying the ECM. The poles and offsets are extracted from the differential thermal voltammetry, differential thermal capacity, and incremental capacity curves as thermoelectric coupling features. Then the internal resistance and thermoelectric coupling features are combined as model inputs. An explanation boosting machine (EBM) is used to construct the SOH estimator according to the good fitting performance and interpretability. The model parameters of EBM are optimized by using an ant colony algorithm to improve its robustness. Finally, comparative experiments between features and the model are carried out on the Oxford dataset. The results demonstrate that the mean absolute error of the proposed method is less than 1%.

Measurement of thermophysical parameters and thermal modeling of 21,700 cylindrical battery

There is temperature unevenness inside the operating battery, and the internal temperature distribution of the battery has gradually attracted attention. To establish a thermal model of the 21,700 cylindrical battery that can reflect the internal temperature distribution, thermophysical parameters including anisotropic thermal conductivity and specific heat capacity are tested through experiments. The thermal model includes the heat generation part and heat transfer part. Thermophysical parameters are essential for the heat transfer part. Hybrid pulse power characterization (HPPC) tests are carried out to obtain battery internal resistance, and the entropy coefficient of the battery is also obtained by tests. Internal resistance and entropy coefficient data are used as inputs for the battery heat generation part. The core temperature and surface temperature of the operating battery are measured by the thermocouple embedded inside the battery and the thermocouple pasted on the battery surface. The calculated core and surface temperatures from the battery thermal model are both in good agreement with the measured temperature results. The maximum core temperature of 2C discharging battery is about 60 °C and the maximum temperature difference inside the 21,700 battery reaches 3 °C. The established simulation model can be used for extended research work. When heat dissipation is enhanced by increasing the convection heat transfer coefficient, the overall temperature of the battery decreases but the temperature non-uniformity inside the battery is aggravated.

Study on Thermal Effect of Aluminum-Air Battery

The heat released from an aluminum-air battery has a great effect on its performance and operating life during the discharge process. A theoretical model was proposed to evaluate the resulting thermal effect, and the generated heat was divided into the following sources: anodic aluminum oxidation reaction, cathodic oxygen reduction reaction, heat production against the battery internal resistance, and hydrogen-evolution reaction. Quantitative analysis was conducted on each part, showing that all heat production sources increased with discharge current density. It should be noted that the heat caused by hydrogen evolution accounted for the most, up to 90%. Furthermore, the regulation strategy for inhibiting hydrogen evolution was developed by addition of hybrid additives to the electrolyte, and the hydrogen-evolution rate was greatly reduced by more than 50% as was the generated heat. This research has important guidance for the thermal effect analysis of aluminum-air batteries, together with control of the thermal management process by inhibiting hydrogen evolution, thus promoting their practical application.

Estimation of battery internal resistance using built-in self-scaling method

This paper proposes the use of the built-in self-scaling (BS) method for the effective estimation of the internal resistance of lithium-ion batteries. The internal resistance is a measure of the battery's state-of-health and an important parameter to monitor, especially in safety-critical applications such as hybrid electric vehicle applications. The BS technique works by identifying the system's impulse response and then computing the resistance from this response. This approach makes use of a prior DC gain which capitalizes on the fact that the state-of-health changes slowly with time. The BS method can be utilized on the fly in real time, is passive, and has high accuracy which is invariant with respect to the battery dynamics. Simulation results show that the BS method reduces the mean square error by factors of 32, 69 and 20 compared with the series resistance, the least squares and data pieces, and the kernel-based techniques, respectively, in the absence of hysteresis. The corresponding values in the presence of hysteresis are 42, 62 and 21, respectively. Experimental results using a lithium nickel manganese cobalt oxide battery and a dynamic current profile based on the Federal Urban Driving Schedule further confirm the superiority of the proposed BS approach.

Rapid Prediction of Retired Ni-MH Batteries Capacity Based on Reliable Multi-Parameter Driven Analysis

In order to solve the problems of long-time consumption and high energy consumption in existing capacity detection methods of retired Ni-MH batteries, a fast and reliable capacity prediction method for retired Ni-MH batteries by multi-parameter driven analysis was proposed in this paper. This method mainly obtains several parameters through short-time measurement and pulse rapid nondestructive testing. Then, Pearson correlation coefficient and KS-test were used to analyze the correlation between the two parameters and verify the same distribution. Finally, SVR was used to predict the battery discharge capacity. The results show that the volume expansion thickness difference Δd, AC internal resistance R, terminal voltage U of the battery, charge and discharge polarization internal resistance Rf1 and Rf2 and pulse charging power P2 of the battery are strongly negatively correlated with the discharge capacity, and these characteristic parameters can effectively and reliably reflect the internal structural characteristics of the battery. Additionally, the mean relative error of the established capacity model is 5.87%, and the lowest error is 1.32%. The prediction effect is good, which provides a certain reference value for the subsequent consistent sorting method.

An Indirect State-of-Health Estimation Method Based on Improved Genetic and Back Propagation for Online Lithium-Ion Battery Used in Electric Vehicles

Lithium-ion battery state of health (SOH) estimation technology is an important part of the design of a battery monitoring system (BMS) for electric vehicles. People often use battery capacity and internal resistance as SOH estimation indicators. However, due to actual working conditions, it is difficult for electric vehicles to achieve complete charge and discharge, so the battery capacity and internal resistance cannot be monitored online. In view of the above questions, this article proposes an indirect SOH estimation method for online EV lithium-ion batteries based on arctangent function adaptive genetic algorithm combination with back propagation neural network (ATAGA-BP). Firstly, constant current drop time (CCDT), constant current drop capacity (CCDC) and maximum constant current drop rate (MCCDR) in constant voltage charging stage are used as health indicator (HI) to evaluate battery SOH in order to indirectly quantify the degradation process of lithium-ion batteries. Error point optimization and correlation verification are also carried out. Secondly, an ATAGA-BP algorithm is proposed to establish the relationship between HI and available battery capacity, and SOH estimate is made for lithium-ion batteries according to the proposed algorithm. Finally, simulation results with NASA data show the correlation between the proposed HI and lithium-ion battery capacity is above 85%, the error of SOH estimation method proposed is 3.7%, and the iteration efficiency is increased by 17.8%.