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1.
For state‐of‐charge (SOC) estimation, the resistance deterioration and continuous capacity loss can lead to erroneous estimation results. In this paper, an SOC estimator of lithium‐ion battery based on the fractional‐order model and adaptive dual Kalman filtering algorithm is proposed first. Then, to improve the accuracy of SOC estimation considering capacity loss, the particle filter algorithm is applied to update capacity online in real time. Then, an SOC estimation method is proposed considering battery capacity loss. The simulation results show that the accuracy of battery capacity prediction based on particle filter is high under the condition of capacity loss. 相似文献
2.
State of charge (SOC) is a vital parameter which helps make full use of battery capacity and improve battery safety control. In this paper, an improved adaptive dual unscented Kalman filter (ADUKF) algorithm is adopted to realize co‐estimation of the battery model parameters and SOC. Notably, the covariance matching method that can adapt the system noise covariance and the measurement noise covariance is used to improve the estimation accuracy. Besides, singular value decomposition (SVD) is utilized to deal with the non‐positive error covariance matrix in both unscented Kalman filters, further enhancing the stability of estimation algorithm. Verification results under Dynamic Stress test and Federal Urban Driving Schedule test indicate that improved ADUKF can achieve more accurate SOC estimates with error band controlled within 2.8%, while that of traditional dual unscented Kalman filter (DUKF) can only be controlled within 5%. Moreover, robustness analysis is also conducted and the validation results present that the proposed algorithm can still provide precise SOC prediction results under some disturbances, such as erroneous initial SOC, inaccurate battery capacity, and various ambient temperatures. 相似文献
3.
Dynamic impact safety of lithium‐ion batteries (LIBs) is a hot subject. The mechanical‐electrical behavior of LIBs under dynamic loading was studied in this study. Drop‐weight tests of two types of indenter, namely, round and flat heads, were conducted. Strain rate and state of charge (SOC) effects on the mechanical properties of LIBs under different indenters were fully discussed. The interaction between mechanical performance and electrical behavior was studied. Experiments show that the structural stiffness of batteries increases with strain rate increase but exhibits little effect from SOC. Different indenters have a significant influence on the mechanical behavior of the prismatic LIBs. Under the same impact rate and SOC, the peak load of a flat head is considerably larger than that of a round head. The battery exhibits a hard short‐circuit under the impact of a round head and a soft short‐circuit under the impact of a flat head. This result shows that the larger the contact area between the indenter and the battery is, the larger the impact load under the same drop‐weight and impact rate will be, although the impact safety of the battery does not decrease. The results provide useful insights into the basic understanding of the electromechanical coupling integrity of LIBs. 相似文献
4.
This study simultaneously considers the state-of-charge (SOC) estimation and model parameter identification of lithium-ion batteries with outliers in measurements. Conventional Kalman-type filters may degrade performance in this case since they assume Gaussian-distributed measurement noise. To improve the SOC estimation accuracy under this condition, a robust normal-gamma (NG)-based adaptive dual unscented Kalman filter (NG-ADUKF) is proposed. First, by modeling the joint distribution of the state and auxiliary variables of the measurement noise as the NG distribution, the unscented Kalman filter (UKF) is integrated with the NG filter to deal with the heavy-tailed measurement noise. Second, the online parameter identification and SOC estimation are realized simultaneously by alternatively using two NG-based adaptive UKFs. The performance of the proposed algorithm is validated by the New European Driving Cycle and Urban Dynamometer Driving Schedule tests. Experimental results show that the proposed NG-ADUKF algorithm has more accurate SOC estimations compared with the dual UKF (DUKF) and the variational Bayes-based adaptive DUKF (VB-ADUKF) in the case of mistuning and outliers. Moreover, the proposed method is more computationally efficient than VB-ADUKF. 相似文献
5.
Lithium‐ion batteries are indispensable in various applications owing to their high specific energy and long service life. Lithium‐ion battery models are used for investigating the behavior of the battery and enabling power control in applications. The Doyle‐Fuller‐Newman (DFN) model is a popular electrochemistry‐based model, which characterizes the dynamics in the battery through diffusions in solid and electrolyte and predicts current/voltage response. However, the DFN model contains a large number of parameters that need to be estimated to obtain an accurate battery model. In this paper, a computationally feasible two‐step estimation approach is proposed that only uses voltage and current measurements of the battery under consideration. In the two‐step procedure, the parameters are divided into 2 groups. The first group contains thermodynamic parameters, which are estimated using low‐current discharges, while the second group contains kinetic parameters, which are estimated using a well‐designed highly‐dynamic pulse (dis‐)charge current. A parameter sensitivity analysis is done to find a subset of parameters that can be reliably estimated using current and voltage measurements only. Experimental data are collected for 12 Ah nickel cobalt aluminum pouch lithium‐ion cell. The voltage predictions of the identified model are compared with several experimental data sets to validate the model. A root mean square error between model predictions and experimental data smaller than 16 mV is achieved. 相似文献
6.
动力电池的荷电状态（SOC）估计作为电池管理系统的核心功能,荷电状态的精确直接影响电动车整车能量管理和动力分配。较为准确的等效电路模型减弱过程噪声的影响,为后续使用扩展卡尔曼滤波算法提高SOC估计精度打下坚实基础。研究以松下NCR18650B动力锂电池为试验对象,建立二阶RC回路的Thevenin等效电路模型,在25 ℃环境下利用修订后的HPPC测试时序、非线性最小乘法进行参数辨识,建立离散状态方程进行SOC估计。结果表明,放电条件下等效电路电压相对误差小于0.01 V,SOC精度较高。 相似文献
7.
State evaluation of battery pack is essential for battery management but laborious when dealing with massive information of cells within the pack. A graphical model for evaluating the status of series‐connected Li‐ion battery pack is established to release the burden. The model is founded by a 2D diagram, with the electric quantity “E” and the capacity “Q” as its axes, therefore called by the “E‐Q diagram.” The new graphical diagram presents the dynamics of cell variations in a linear way, thereby benefiting the design and management of battery pack, including (1) quantifying the cell variations by region, (2) illustrating the evolution of cell variations during aging, (3) guiding the estimation of pack states considering algorithm error in cell states, and (4) solving the balancing problem. The experimental results conform to the theoretical analysis, indicating that the E‐Q diagram will be pervasively applied in the design and management of series‐connected battery pack. Moreover, the E‐Q diagram is suitable for education on the basics of a battery pack, because it is a graphical model. 相似文献
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Temperature affects the performance of electric vehicle battery. To solve this problem, micro heat pipe arrays are utilized in a thermal management system that cools and heats battery modules. In the present study, the heat generation of a battery module during a charge‐discharge cycle under a constant current of 36 A (2C) was computed. Then, the cooling area of the condenser was calculated and experimentally validated. At rates of 1C and 2C, the thermal management system effectively reduced the temperature of the module to less than 40°C, and the temperature difference was controlled less than 5°C between battery surfaces of the module. A heating plate with 30‐W power effectively improved charge performance at low temperature within a short heating time and with uniform temperature distribution. Charge capacity obviously increased after heating when battery temperature was below 0°C. This study presents a new way to enhance the stability and safety of a battery module during the continuous charge‐discharge cycle at high temperatures and low temperatures accordingly. 相似文献
10.
Seunghun Jung 《国际能源研究杂志》2016,40(8):1073-1084
Electrode morphology has significant influence on the performance of lithium‐ion batteries in that it controls electrical conductivity and electrode utilization by establishing electrical connectivity in the electrode. The present study investigates the effect of the electrode morphology on battery performance by combining two different mathematical models. First, a two‐dimensional, direct numerical simulation (DNS) model is introduced, which stochastically generates electrode morphology and calculates electrical conduction and electrode utilization. Various simulations are conducted to evaluate the effect of the active particle coating, conductive agent loading, particle size, and electrode compression by using the DNS model. Second, data acquired from the DNS model are applied to the blended‐electrode model to evaluate battery performance. Calculation result confirms that electrode morphologies have significant effects on both capacity and power of lithium‐ion batteries. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
11.
Development of high-fidelity mathematical models and state-of-charge (SOC) estimation of Li-ion battery becomes a significant challenge when the temperature effects are considered. In this paper, we propose an enhanced temperature-dependent equivalent circuit model for a Li-ion battery and applied it for battery parameters estimation and model validation, as well as SOC estimation. First, the new battery model is elaborated, including a newly integrated resistance-capacitor structure, a static hysteresis voltage and a temperature compensation voltage term. The forgetting factor least square approach is utilized to realize the parameter identification. Next, the proposed battery model is employed to estimate battery SOC by incorporating the extended Kalman filter algorithm. Finally, simulation results are provided to demonstrate the superior performance of the proposed battery model in comparison with the common first-order Thevenin temperature model. Compared with Thevenin model, the maximal values of relative reconstruction error and root mean squared error with the proposed battery model are decreased by about 33.3% and 50.0%, respectively, for the battery terminal output voltage, 50.0% and 53.0%, respectively, for the SOC estimation, under three different test profiles. 相似文献
12.
Thermal management of Li‐ion cells is an important technological problem for energy conversion and storage. Effective dissipation of heat generated during the operation of a Li‐ion cell is critical to ensure safety and performance. In this paper, thermal performance of a cylindrical Li‐ion cell with an axial channel for coolant flow is analyzed. Analytical expressions are derived for steady‐state and transient temperature fields in the cell. The analytical models are in excellent agreement with finite‐element simulation results. The dependence of the temperature field on various geometrical and thermal characteristics of the cell is analyzed. It is shown that coolant flow through even a very small diameter axial channel results in significant thermal benefit. The trade‐off between thermal benefit and reduction in cell volume, and hence capacity due to the axial channel, is analyzed. The effect of axial cooling on geometrical design of the cell, and transient thermal performance during a discharge process, is also analyzed. Results presented in this paper are expected to aid in the development of effective cooling techniques for Li‐ion cells based on axial cooling. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
13.
The development of a novel method to estimate the state of charge (SOC) with low read‐only memory (ROM) occupancy, high stability, and high anti‐interference capability is very important for the battery management system (BMS) in actual electric vehicles. This paper proposes the square root cubature Kalman filter (SRCKF) with a temperature correction rule, based on the BMS of a common on‐board embedded micro control unit (MCU), to achieve smooth estimation of SOC. The temperature correction rule is able to reduce the testing effort and ROM space used for data table storage (189.3 kilobytes is much smaller than the storage of the MPC5604B, with 1000 kilobytes), while the SRCKF is adopted to achieve highly robust real‐time SOC estimation with high resistance to interference and moderate computing cost (68.3% of the load rate of the MPC5604B). The results of multiple experiments show that the proposed method with less computational complexity converges rapidly (in approximately 2.5 s) and estimates the SOC of the battery accurately under dynamic temperature condition. Moreover, the SRCKF algorithm is not sensitive to the high measuring interference and highly nonlinear working conditions (even with 1% current and voltage measurement disturbances, the root mean square error of the proposed method can be as high as 0.679%). 相似文献
14.
储能电池在新能源并网、新能源汽车等产业领域发挥着重要作用,为了对电池进行有效地控制与管理,需要配备必要的电池管理系统,电池荷电状态（SOC）是其中最为重要的一环。磷酸铁锂（LiFePO4,LFP）电池SOC与多个影响因素密切相关,呈强非线性,本文重点归纳温度对磷酸铁锂电池SOC的影响。首先将工作温度对开路电压、实际容量、充放电效率、自放电率及电池老化等电池特性的影响进行归纳总结,随后通过对工作温度的影响规律进行分析、总结和归纳,基于经典“开路电压 + 安时积分”法将温度参数直接或间接引入到SOC的实时估算模型中,得到考虑温度参数的新模型,进而提高电池SOC的估算精度。 相似文献
15.
LiFePo4 battery is widely used in electric vehicles; however, its flatness and hysteresis of the open‐circuit voltage curve pose a big challenge to precise state of charge (SOC) estimation. The issue is discussed and addressed in this paper. First, a cell model with hysteresis is built to describe real‐time dynamic characteristics of the LiFePo4 battery. Second, the model parameters and SOC are estimated independently to avoid the possibility of cross interference between them. For model identification, an adaptive unscented Kalman filter (AUKF) algorithm is used to identify the cell parameters as they change slowly. While SOC could change rapidly, wavelet transform AUKF algorithm is put forward to estimate SOC. In the novel algorithm, the measurement noise can be estimated and updated online. Finally, the performance of the proposed method is verified under dynamic current condition. The experimental results show that estimated value based on the proposed method is more accurate than unscented Kalman filter‐based method and AUKF‐based algorithm. Meanwhile, the proposed estimator also has the merits of fast convergence and good robustness against the initialization uncertainty. 相似文献
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Faced with the ever-increasing urban environmental pollution, the electric vehicles (EVs) have received increasing attention in the automotive industry. Lithium-ion batteries, serving as electrochemical power storage, have been extensively used in EVs because of the lightweight, no local pollution and high power density. The increasing awareness on the safe operation and reliability of the battery requires an efficient battery management system (BMS), among the parameters monitored by which, state-of-charge (SOC) is critical in preventing overcharge, deep discharge, and irreversible damage. This article investigates the neural network (NN)-based modeling, learning, and estimation of SOC by comparing two different methodologies, that is, direct structure with SOC as network output and indirect structure with voltage as output. Firstly, the nonlinear autoregressive exogenous neural network (NARX-NN) is introduced, in which SOC is directly deemed as an NN output for learning and estimation. Secondly, a radial basis function (RBF)-based NN with unscented Kalman filter (RBFNN-UKF) is proposed, in which the terminal voltage is used as output. Instead, SOC is deemed as an internal state which would be estimated indirectly based on the feedback error of voltage. Experimental results demonstrate that both estimators can achieve accurate SOC estimation for regular cases, in spite of the inaccurate initial conditions. However, the direct NN structure is revealed as not capable of dealing with the cases with sensor bias, which, however, can be well accommodated in the indirect structure by extending the sensor bias as an augmented state. Benefiting from the uncertainty augmentation and feedback compensation, the indirect RBFNN-UKF shows superiority over the direct estimation in the practical experiments, depicting a promising prospect in the future onboard EV-BMS application. 相似文献
18.
Large amount of heat generated during an external short circuit (ESC) process may cause battery safety events. An experimental platform is established to explore the battery electrothermal characteristics during ESC faults. For 18650‐type nickel cobalt aluminum (NCA) batteries, ESC fault tests of different initial state of charge (SOC) values, different external resistances, or different ambient temperatures are carried out. The test case of a smaller external resistance is characterized by a shorter ESC duration with a faster cell temperature rise, whereas the case of a larger external resistance will last for a longer duration, discharge more electricity, and terminate in a slightly higher temperature. The tested batteries of high initial SOCs generally have higher temperature rise rates, smoother changes at the output current/voltage curves, but a smaller discharged capacity. The batteries of low initial SOCs can be overdischarged by the ESC operations. At low temperatures, say 0°C, the ESC process outputs much less electricity than the process at high temperatures, eg, 30°C. The initial low temperature has little effect on reducing the battery overheat due to ESC operations. The battery thermal behavior is of hysteresis property; analysis of heat generations reveals the subsequent increase of battery surface temperature after the completion of ESC discharge is due to the battery material abusive reaction heats. It is found from analytical and numerical analyses that there can have approximately 30°C temperature difference between the battery core and its surface during ESC operations. The interruption of ESC operation is very probably caused by the high battery core temperature, which leads to the destruction of solid‐electrolyte interface (SEI) film. 相似文献
19.
硅基材料由于具有超高的理论比容量,安全的嵌锂工作电位和廉价易得等诸多优点,是下一代高比能量电池体系最理想的负极材料。尽管硅基材料的研究已经进行很长时间,但是硅基材料嵌锂时巨大的体积膨胀,循环性能较差等问题一直难以得到有效解决。开发高性能硅基负极黏结剂是解决硅基材料应用问题的重要途径之一,具有“刚柔并济”结构特性的黏结剂分子能够有效抑制硅基材料结构膨胀粉化,保持电极导电网络的完整性,从而有效提升其循环性能。本文综述了硅基负极黏结剂的特性要求,新型硅基负极黏结剂的研究进展,并对该领域未来潜在的研究方向进行了展望：复合体系聚合物黏结剂的开发;特殊空间构型黏结剂的开发;新型导电黏结剂的开发;自支撑无黏结剂硅基负极的开发。 相似文献
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为了准确和方便地研究混合动力汽车中的磷酸铁锂动力电池的性能,基于Thevenin电池模型,考虑了温度对模型的影响,通过库仑计数法估算电池荷电状态（SOC）。针对该电池,通过HPPC试验识别电池模型参数,在Matlab/Simulink中建立物理仿真模型进行仿真计算。研究表明：所使用的Thevenin电池模型精度高,对比模拟和实测端电压结果,两者变化趋势基本相同,端电压平均误差为3.6 V,最大误差为12.6 V,占电池额定电压0.79%,能真实的模拟电池充放电特性;结合库仑计数法计算电池SOC,能有效控制SOC的估算值在高精度范围内。模拟SOC和实测SOC结果进行对比表明,SOC精度保持在3%以内。 相似文献