安时-卡尔曼交叉运行的电池荷电状态估算策略及其微控制器在环验证

为了提高电池管理系统(BMS)的性能,研究了电池荷电状态(SOC)的估算方法,并根据SOC估算算法精度和系统实时性要求,提出了安时(AH)积分算法-卡尔曼(Kalman)算法(AH-Kalman)交叉运行的SOC估算策略。该策略用开路电压(OCV)法确定SOC初值,以实时性较强的AH积分法为主,采用间歇运行的Kalman滤波法修正安时计量法积分误差。建立了系统仿真模型,验证了卡尔曼滤波算法对安时积分法积累误差的修正作用。将控制算法生成C代码下载到目标控制器,搭建微控制器在环测试验证(PILS)平台,进行了与传统卡尔曼滤波算法的复杂度对比分析。结果表明,所提出AHKalman交叉运行的SOC估算策略在保证了SOC估算精度的同时也具有较好的实时性,便于实际应用。     

基于改进型能量守恒SOC估算法的电动汽车三段式智能充电方式研究

为研究电动汽车安全、快速的智能充电方式,基于传统能量守恒法,考虑电池容量衰减和电池内阻损失对荷电状态(state of charge,SOC)估算的影响,提出改进型能量守恒SOC估算方法。对比分析几种传统充电方式,根据马斯定理确定最佳充电电流,提出以改进型能量守恒SOC估算法得到的SOC值作为判断依据的电动汽车三段式(小电流充电、脉冲充电、恒压充电)智能充电方式,并建立其仿真模型。结果表明:改进型能量守恒SOC估算法得到的SOC值要小于传统能量守恒法,其更加接近真实SOC值;三段式智能充电方式能根据电池组SOC值的变化智能地选择具体充电方式,实现了对电池的安全、快速充电。提出的基于改进型能量守恒SOC估算的三段式智能充电方式对当前电动汽车充电方式的研究提供了一定的参考价值,为智能充电方式研究效能的提升提供了一种可行方法,也为智能充电理论应用于工程实践打下基础。     

基于WOA-UKF算法的锂电池容量与SOC联合估计

锂电池的荷电状态(SOC)和有效容量是表征电池当前剩余电量和电池寿命的重要参数,提出一种锂离子电池有效容量和SOC的联合估计方法。在电池全寿命周期内,给出一种开路电压与SOC和电池有效容量非线性模型的两变量多项式描述;当电池循环使用次数超过预设值,采用鲸鱼优化算法估计当前电池容量与电池模型参数,根据模型参数与容量值采用无迹卡尔曼滤波器估计电池SOC;在SOC估计过程中,采用鲸鱼优化算法更新无迹卡尔曼滤波器的观测噪声方差和过程噪声方差,实现噪声方差的自适应调节,进而提高估计精度。实验结果验证了该方法的有效性和联合估计方案的可行性。     

Modeling and state of charge estimation of lithium-ion battery

Modeling and state of charge(SOC) estimation of lithium-ion(Li-ion) battery are the key techniques of battery pack management system(BMS) and critical to its reliability and safety operation.An auto-regressive with exogenous input(ARX) model is derived from RC equivalent circuit model(ECM) due to the discrete-time characteristics of BMS.For the time-varying environmental factors and the actual battery operating conditions,a variable forgetting factor recursive least square(VFFRLS)algorithm is adopted as an adaptive parameter identification method.Based on the designed model,an SOC estimator using cubature Kalman filter(CKF) algorithm is then employed to improve estimation performance and guarantee numerical stability in the computational procedure.In the battery tests,experimental results show that CKF SOC estimator has a more accuracy estimation than extended Kalman filter(EKF) algorithm,which is widely used for Li-ion battery SOC estimation,and the maximum estimation error is about 2.3%.     

基于RFF及GWO-PF的锂电池SOC估计

为了提高锂电池剩余电量估计的准确性,提出一种在线参数辨识与改进粒子滤波算法相结合的锂电池SOC估计方法。针对粒子滤波中的粒子退化问题,引入灰狼算法,利用灰狼算法较强的全局寻优能力优化粒子分布,保证粒子多样性,有效抑制粒子退化现象,提高滤波精度。采用带遗忘因子的递推最小二乘法实时更新模型参数,并与改进粒子滤波算法交替运行,进一步提高SOC的估计精度。实验结果表明,改进算法的平均估计误差始终保持在±0.15%以内,相比扩展卡尔曼滤波与无迹卡尔曼滤波算法,在电池SOC估计上有更高的估计精度与稳定性。     

基于改进无迹卡尔曼滤波的锂电池SOC在线估计

针对无迹卡尔曼滤波算法对电池模型敏感并且容易受到不确定噪声干扰的问题,提出了改进的无迹卡尔曼滤波算法（improved unscented Kalman filter,IUKF）,提高电池荷电状态（State of charge,SOC）估计精度和鲁棒性能。首先,对锂离子电池进行建模并完成参数离线辨识。紧接着,对模型参数进行敏感性分析,研究不同参数对SOC估计效果的影响程度,为模型参数自适应对象的选取提供依据。随后,研究了包含模型自适应算法和噪声自适应算法在内的IUKF算法实现过程。最后,通过物理实验对比分析了IUKF与其它算法的实际估计效果,实验结果表明,该方法估计误差小于1.79%,鲁棒性能良好。     

Improved estimation of residual capacity of batteries for electric vehicles

Abstract

This paper proposes an improved means of estimation for the residual capacity of lead‐acid batteries used in electric vehicles. The residual capacity of batteries in commercial products is usually indicated by the state of charge (SOC) of the battery set, in terms of the measurement of amp‐hours, or roughly an instant voltage. More practical and accurate SOC in the operation of electric vehicles must consider the original capacity when the battery is first installed, capacity deficiency due to high discharge rate, capacity dissipated in internal resistance, and correcting parameters for the battery aging process. The proposed estimation techniques include the amp‐hours measurement weighted by a correction function of various discharge rates, the transient open‐circuit voltage measurement to compensate for the energy dissipation from internal resistance, and the reset of parameters in the linear function of SOC and open‐circuit voltage for the aging effect. A monitoring circuit with a programmable logic chip is implemented, and the experimental results show that a more accurate indication of SOC is achieved using the modified estimation techniques, namely a weighted ampere‐hour measurement with transient open‐circuit voltage combined with the aging effect.     

未知输入干扰下异构多传感器分布式两级信息滤波与偏差联合估计

针对目标跟踪过程中受未知输入影响的多传感器网络,提出一种局部单传感器抗干扰信息滤波算法并根据此算法实现分布式一致性多传感器融合滤波估计实现目标的精确跟踪。首先,建立包含未知输入的系统模型;其次,消除未知输入影响并设计局部单传感器两级信息滤波算法实现状态和广义偏差的同时估计;最后,根据提出的单传感器两级信息滤波算法进行分布式加权数据融合。仿真结果表明,该方法及其融合算法的系统偏差、状态估计误差和均方根误差均明显降低,目标跟踪精度有所提高,并且具有较低的运算量和较高的一致性。     

Recent Advances in Energy Chemical Engineering of Next-Generation Lithium Batteries

Rechargeable lithium-ion batteries (LIBs) afford a profound impact on our modern daily life. However, LIBs are approaching the theoretical energy density, due to the inherent limitations of intercalation chemistry; thus, they cannot further satisfy the increasing demands of portable electronics, electric vehicles, and grids. Therefore, battery chemistries beyond LIBs are being widely investigated. Next-generation lithium (Li) batteries, which employ Li metal as the anode and intercalation or conversion materials as the cathode, receive the most intensive interest due to their high energy density and excellent potential for commercialization. Moreover, significant progress has been achieved in Li batteries attributed to the increasing fundamental understanding of the materials and reactions, as well as to technological improvement. This review starts by summarizing the electrolytes for next-generation Li batteries. Key challenges and recent progress in lithium-ion, lithium–sulfur, and lithium–oxygen batteries are then reviewed from the perspective of energy and chemical engineering science. Finally, possible directions for further development in Li batteries are presented. Next-generation Li batteries are expected to promote the sustainable development of human civilization.     

A new approach for estimating parameters of two-parameter bathtub-shaped lifetime distribution under modified progressive hybrid censoring

The lifetime distributions with bathtub-shaped hazard rate functions and censoring scheme have been used widely in life testing and reliability engineering. This paper develops a new approach for estimating parameters of an important two-parameter lifetime data analysis model with bathtub-shaped hazard rate function under the assumption that sample is modified progressively hybrid censored. One of the most frequently used methodologies, maximum likelihood (ML) estimation, is used for estimating unknown parameters. The estimates of unknown parameters are proposed using popular Newton–Raphson algorithm because the estimators cannot be obtained in closed forms. It is well known that the convergence of Newton–Raphson algorithm is affected by an initial point. Therefore, a new Newton–Raphson algorithm with an adaptive initial point within the exact joint confidence region has been suggested to compute the ML estimation. Extensive numerical simulations show that the proposed algorithm converges all the times and it is effective. Finally, one real-world data set from engineering is analysed to illustrate the application of the proposed  method.     

Mott–Schottky Effect in Core–Shell W@WxC Heterostructure: Boosting Both Electronic/Ionic Kinetics for Lithium Storage

The dynamics rate of traditional metal carbides (TMCs) is relatively slow, severely limiting its fast-charging capacity for lithium-ion batteries (LIBs). Herein, the core–shell W@W_xC heterostructure is developed to form Mott–Schottky heterostructure, thereby simultaneously accelerating the electronic and ionic transport kinetics during the charging/discharging process. The W nanoparticles are partially reduced into W_xC to form a particular core–shell structure with abundant heterogeneous interfaces. Benefiting from the Mott–Schottky effect, the electrons at the metal/semiconductor heterointerface can migrate spontaneously to realize an equal work function on both sides. In addition, the independent nanoparticle as well as the unique core–shell structure facilitate the ionic diffusion kinetics. As expected, the W@W_xC electrode exhibits excellent electrochemical stability for LIBs, whose capacity can be maintained at 173.8 mA h g⁻¹ after 1600 cycles at a high current density of 5 A g⁻¹. When assembled into a full cell, it can achieve an energy density of 360.2 Wh kg⁻¹. This work presents a new avenue to promote the electronic and ionic kinetics for LIBs anodes by constructing the unique Mott–Schottky heterostructure.     

基于IALO算法的蓄电池参数辨识

合理的等效电路模型及准确的模型参数对蓄电池荷电状态(SOC)的准确估计具有重要影响。针对蓄电池三阶Thevenin等效电路模型,基于改进蚁狮优化算法,提出了一种模型参数辨识方法。引入混沌Logistic映射初始化,使初始化群体遍及解空间,有利于寻找全局最优解;引入自适应惯性权重加随机柯西变异策略,有效提高了算法收敛速度;引入精英反向学习策略,有效提高了群体的多样性,避免算法陷入局部最优解。5个测试函数的测试结果表明:相比于蚁狮优化算法、粒子群算法与樽海鞘优化算法,改进蚁狮优化算法收敛速度更快,精度更高。对蓄电池三阶Thevenin等效电路模型进行参数辨识,结果表明:改进蚁狮优化算法相比蚁狮优化算法具有更高的辨识精度。     

基于混合有限差分格式的非线性奇异摄动问题的最大范数的后验误差估计

自适应移动网格算法在奇异摄动微分方程的数值解法中占有非常重要的地位,其关键技术是构造出有效的离散格式和相应的后验误差估计。基于此,对一类带参数的一阶非线性奇异摄动初值问题,给出了其连续解的稳定性估计及相关推论。然后,在任意非均匀网格上,利用向后欧拉公式和一阶中心有限差分格式建立了一个混合有限差分格式,并严格分析了离散解的稳定性。同时,基于连续解的稳定性估计和分段线性插值技术,推导出混合有限差分格式的最大范数的后验误差估计。利用该后验误差估计选择了一个最优的网格控制函数,并结合网格等分布原理设计了一个自适应网格生成算法。最后的数值实验验证了自适应移动网格算法的有效性,且算法的平均收敛阶可达到二阶。数值结果进一步表明自适应移动网格的误差明显小于 Shishkin 网格的误差,且其收敛阶也高于 Shishkin 网格计算得到的收敛阶。     

弹性波主动控制中LMS算法的最佳收敛系数问题研究

对扭转弹性波的主动控制系统以及LMS算法进行了描述。通过对直轴中扭转弹性波主动控制的仿真计算，讨论了LMS算法中的收敛系数对控制系统收敛时间的影响。重点讨论了弹性波控制中误差传递途径相对于主激励源的时间延迟与收敛系数以及收敛时间的关系，并回归出最佳收敛系数与延迟时间之间的倒数关系。同时通过对期望信号和误差信号当量传递函数的研究，从理论上确定了最佳收敛系数与延迟时间的关系，两者的研究结果是一致的。     

基于干扰观测器的鲁棒高精度转速估计方法

 动态转速的高精度测量是高性能运动控制中的重要问题,尤其对于低速运动情况.针对该问题,提出一种新型实时转速估计方法,对系统外部扰动和建模误差,采用扰动观测器进行估计,再将其输出引入转速观测器,从而保证转速估计的收敛性,并增强其鲁棒性.以直流高精度伺服系统为例,进行了仿真和实验研究,结果表明该方法有效,鲁棒性强,且对角位置量化噪声不敏感.     

永磁同步电机全速范围内无传感控制策略研究

目的 为了提高自动化包装生产线的产品效率和质量,改善永磁同步电机无速度传感器矢量控制系统的性能,针对电机运行于低速时反电动势不易检测以及高速位置精度较低的问题,设计一种基于高频方波注入法和改进滑模观测器的复合观测器。方法 在低速时采用高频方波信号注入法来实现对转子位置信息的估计,在中高速时采用改进的滑模观测器来估计转子位置,通过引入双边界层切换函数和可变滑模增益来加快收敛速度和减小抖振,同时设计基于单神经元PI的锁相环用来解析转子信息,进而提高速度和位置,估计精度。结果 通过与单一的算法进行对比分析,发现复合观测器的位置估算精度得到了提高。结论 Matlab/Simulink仿真实验以及实物验证结果表明,和传统的算法相比,该算法具有位置估计精度高、鲁棒性好等优点。     

Stabilization of Sn Anode through Structural Reconstruction of a Cu–Sn Intermetallic Coating Layer

The metallic tin (Sn) anode is a promising candidate for next-generation lithium-ion batteries (LIBs) due to its high theoretical capacity and electrical conductivity. However, Sn suffers from severe mechanical degradation caused by large volume changes during lithiation/delithiation, which leads to a rapid capacity decay for LIBs application. Herein, a Cu–Sn (e.g., Cu₃Sn) intermetallic coating layer (ICL) is rationally designed to stabilize Sn through a structural reconstruction mechanism. The low activity of the Cu–Sn ICL against lithiation/delithiation enables the gradual separation of the metallic Cu phase from the Cu–Sn ICL, which provides a regulatable and appropriate distribution of Cu to buffer volume change of Sn anode. Concurrently, the homogeneous distribution of the separated Sn together with Cu promotes uniform lithiation/delithiation, mitigating the internal stress. In addition, the residual rigid Cu–Sn intermetallic shows terrific mechanical integrity that resists the plastic deformation during the lithiation/delithiation. As a result, the Sn anode enhanced by the Cu–Sn ICL shows a significant improvement in cycling stability with a dramatically reduced capacity decay rate of 0.03% per cycle for 1000 cycles. The structural reconstruction mechanism in this work shines a light on new materials and structural design that can stabilize high-performance and high-volume-change electrodes for rechargeable batteries and beyond.     

双线性时间序列模型的参数辨识

导出了双线性时间序列模型参数预报误差估计的递推算法，采用伴随常微分方程的稳定性分析方法分析了双线性模型的ｍ－可逆性对可预报误差估计算法收敛性的影响，并给出了相应的仿真示例。     

Micrograting design to retrieve IR spectra in the long wavelength region

To design microgratings, which can be used for correlation spectroscopy in the 725–1450 cm^?1 range, a gradient searching Davidon–Fletcher–Powell (DFP) algorithm was successfully applied to retrieve target spectra of SF₆, ethylene, SO₂, and NH₃. Owing to a unique fit parameter treatment, the DFP algorithm produced stable convergence for the minimization and provided superior matches between the diffraction spectrum and the target spectrum to those provided by the phase retrieval algorithm (PRA) or the extended PRA. In addition, the diffraction efficiencies for the micrograting line profiles obtained from the DFP algorithm were at least an order of magnitude greater than those from the PRA or the extended PRA. We also evaluated the effects of number of line element reduction or the dimensional errors in the line elements on the spectrum shape. The line depth error would not change the main spectral features but increase noise features. However, the line width error affects more sensitively the spectrum shape and the diffraction efficiency.     

Altitude and roll control of a hovering quad-rotor air vehicle using the multi-objective approximate optimization of proportional–integral–differential control

This study explores the optimal proportional–integral–differential (PID) gains of a hovering quad-copter to allow recovery from disturbed altitude and roll positions. Computational fluid dynamics was used to determine the rotor distance and the blade shape parameters for maximizing the hovering thrust. Using a six-degree-of-freedom quad-copter dynamics model, a control algorithm was then used to obtain PID gains. The PID control was approximated using back-propagation neural networks (BPNs). Position control of the quad-copter model was performed by determining the optimal PID gains required to minimize the control duration for altitude and roll. The non-dominated sorting genetic algorithm (NSGA-II) was used for multi-objective optimization and a BPN was used for meta-modelling the PID control. The PID gains generated from bi-objective optimal designs were compared with the initial design. The results confirmed that the recovery time from an unbalanced position was reduced and that the motion of the quad-copter was better stabilized.