电动汽车锂离子电池荷电状态估算方法研究综述

锂离子电池具有循环寿命长、能量密度高、自放电率低、环境污染小等优点,在电动汽车产业中得到广泛应用。电动汽车中的电池管理系统(BMS)可以维护和监测电池状态,确保电池的安全性和可靠性。电池荷电状态(SoC)表示电池中剩余的电量,是BMS的重要参数之一,实时精确的SoC估算可以延长电池寿命,保障行驶安全。然而锂离子电池是一个高度复杂的非线性时变系统,电池寿命、环境温度、电池自放电等许多未知因素均会对估算精度造成影响,使估算难度大大增加。为了满足不同条件下对锂离子电池SoC精确、快速、实时估算的要求,需要对SoC估计算法进行进一步研究与改进。近年来已有相关文献对锂离子电池SoC的估算方法进行了综述,然而已有相关综述对估算方法的总结不够全面且缺少流程表达。该文首先介绍了锂离子电池的工作原理,阐述了影响电池SoC估算的因素;其次,通过总结最新的研究成果对电池SoC估算方法进行了归纳分析,根据各类算法的不同特性将其分为查表法、安时积分法、基于模型的方法、数据驱动的方法以及混合方法五大类,说明了各类估算方法的主要特征并对模型或算法的优缺点进行综合的比较和讨论;最后,对电动汽车中锂离子电池SoC估算方法的未来发展方向做出展望。     

Channel estimation with ISFLA based pilot pattern optimization for MIMO OFDM system

In multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) systems, the channel state information should be known by the receiver for obtaining transmitted data. Channel estimation algorithms are used to examine the multipath effects of frequency selective Rayleigh fading channels. In this paper, Compressed Sensing (CS) based channel estimation technique is considered for reconstructing the signal with improved spectral efficiency. It requires transmitting the known pilot data to the receiver for estimating channel information. The optimum pilot patterns are selected through reducing the mutual coherence of measurement matrix. In order to maximize the accuracy of sparse channel estimation and to reduce the computational complexity, an optimization algorithm Improved Shuffled Frog Leaping (ISFL) is proposed. When compared with the traditional estimation methods like least squares (LS), and minimal mean square error (MMSE), 4.7% of spectral efficiency is increased with ISFLA based channel estimation. Implementation results show that, by using the proposed algorithm, the bit error rate (BER) and Mean Square Error (MER) performance of the system is increased with 1.5 dB and 2 dB respectively.     

Chromatic dispersion estimation methods using polynomial fitting in PDM-QPSK or other multilevel-format coherent optical systems

We propose a polynomial fitting algorithm based method for non-data-aided chromatic dispersion (CD) estimation in single carrier (SC) coherent optical systems with arbitrary modulation formats, and compare it with our previously proposed CD estimation method which is also based on the polynomial fitting algorithm but requires special modulation formats thus is a data-aided CD estimation method for systems with PDM-QPSK or other multilevel modulation formats. For the data-aided CD estimation method, an extra chirp-free OOK signal is transmitted. The curve of the average phase at the frequency ± f as a function of the frequency f is measured at the coherent receiver. The accumulated CD is then estimated with a polynomial fitting algorithm. In the simulation of a 50 Gbaud 50%-RZ OOK system through 12.5 × 80 km standard single mode fiber (SSMF), the estimation errors are within ± 50 ps/nm in 20 tests when the launch power is from −5 dBm to −1 dBm. Non-data-aided CD estimation for arbitrary modulation formats is achieved by measuring the differential phase between frequency f ± f_s/2 (f_s is the symbol rate) in digital coherent receivers. The estimation errors are within ± 200 ps/nm, in a 50 Gbaud PDM-QPSK system through 10 × 80 km SSMF with the launch power from −3 dBm to −1 dBm. The estimation accuracy can be potentially improved by averaging multiple results. The data-aided CD estimation method has an inherently bigger estimation range than that of the newly proposed non-data-aided method, while the newly proposed non-data-aided method can tolerate a much larger frequency offset between the transmitter and the local oscillator. These methods are promising for future optical fiber networks with dynamic optical routing and coherent detection.     

动力型锂电池SOC与SOH协同估计

锂电池及其应用近年来逐渐成为研究热点。以提高电池管理系统(BMS)对电池荷电状态(SOC)和健康状态(SOH)的估算精确度为目标,在建立二阶Thevenin等效电路模型基础上提出一种能在线协同估算电池荷电状态和健康状态的改进扩展卡尔曼滤波算法。通过分阶段脉冲放电实验,并利用最小二乘法求得模型参数。在动态应力测试工况(DST)下借助Matlab对比分析了改进扩展卡尔曼算法在SOC和SOH估计精确度、错误初值时算法收敛性、算法复杂度等方面的性能。实验表明,利用该算法可以精确估计出各采样点处的SOC和SOH,误差低于1%;且在初值不准确情况下,运行算法可快速收敛至真值附近,算法估算结果的准确性与模型参数的微调无关,鲁棒性较好。     

Motion Compensated Three-Dimensional Frequency Selective Extrapolation for improved error concealment in video communication

During transmission of video data over error-prone channels the risk of getting severe image distortions due to transmission errors is ubiquitous. To deal with image distortions at decoder side, error concealment is applied. This article presents Motion Compensated Three-Dimensional Frequency Selective Extrapolation, a novel spatio-temporal error concealment algorithm. The algorithm uses fractional-pel motion estimation and compensation as initial step, being followed by the generation of a model of the distorted signal. The model generation is conducted by an enhanced version of Three-Dimensional Frequency Selective Extrapolation, an existing error concealment algorithm. Compared to this existent algorithm, the proposed one yields an improvement in concealment quality of up to 1.64 dB PSNR. Altogether, the incorporation of motion compensation and the improved model generation extends the already high extrapolation quality of the underlying Frequency Selective Extrapolation, resulting in a gain of more than 3 dB compared to other well-known error concealment algorithms.     

A 1-V, 1.2-mA fully integrated SoC for digital hearing aids

Both power and size are very important design issues for hearing aids. This paper proposes a fully integrated low-power SoC for today׳s digital hearing aids. The SoC integrates all the audio processing elements on single chip, including the analog front-end, digital signal processing (DSP) platform and class-D amplifier. Also, the low-dropout voltage regulators and internal clock generator are both integrated to minimize the system overall size. The 24-bit DSP platform comprises an application-specific instruction-set processor and several dedicated accelerators to achieve a trade-off between flexibility and power efficiency. Three critical hearing-aid algorithms (wide dynamic range compression, noise reduction and feedback cancellation) are performed by the low-power accelerators. The proposed SoC has been fabricated in SMIC 130 nm CMOS technology. The measurement results show that the analog front-end has up to 88 dB signal-to-noise ratio. And the DSP platform consumes about 0.86 mA current at 8 MHz clock frequency when executing the three algorithms. The total current consumption of SoC is only 1.2 mA at 1 V supply. In addition, the acoustic test results indicate that the SoC is one promising candidate for hearing-aid manufacturers.     

A fine-grain distortion and complexity aware parameter tuning model for the H.264/AVC encoder

Most existing video encoders currently used in mobile applications are unable to gracefully degrade their output quality as the battery life nears its end. In other words, they cannot manage power consumption to efficiently utilize the available power resources. To be able to effectively adapt to changes in the encoder′s software and hardware platforms, especially due to the power limitations of mobile devices, the effect of encoder parameters on the encoding quality and power consumption has to be represented using a Rate–Distortion–Complexity (R–D–C) model. Most existing R–D–C models only consider macroblock level parameters, and overlook other higher level parameters that may have a more significant impact on complexity. In this paper, the distortion and complexity of the H.264/AVC encoder is controlled considering a subset of higher level encoding parameters consisting of search range, number of reference frames, and motion vector resolution. First, the complexity of full and fast motion estimation methods is modeled in an implementation and platform independent manner. Then, using this complexity model, a common encoding parameter setting table is derived, which leads to the least amount of distortion for each complexity condition. Finally, a complexity control mechanism is proposed which tunes the encoding parameters in a real-time manner. The proposed model can be combined with other existing macroblock level models in order to design a two-phase fine grain complexity controller. Simulation results indicate that when our method is integrated with the direct resource allocation (DRA) approach, performance increases by an average of 1.02 dB and 1.06 dB for full and fast motion estimation approaches, respectively.     

Improved interview video error concealment on whole frame packet loss

An improved DIBR-based (Depth image based rendering) whole frame error concealment method for multiview video with depth is designed. An optimal reference view selection is first proposed. The paper further includes three modified parts for the DIBRed pixels. First, the missing 1-to-1 pixels are concealed by the pixels from another view. The light differences between views are taken care of by the information of the motion vector of the projected coordination and a reverse DIBR procedure. Second, the generation of the many-to-1 pixels is improved via their depth information. Third, the hole pixels are found using the estimated motion vectors derived efficiently from a weighted function of the neighboring available motion vectors and their distance to the target hole pixel. The experimental results show that, compared to the state-of-the-art method, the combined system of the four proposed methods is superior and improves the performance by 5.53 dB at maximum.     

Cycle life estimation of lithium-ion polymer batteries using artificial neural network and support vector machine with time-resolved thermography

A battery cycle life forecast method without requirements of contact measurement devices and long testing time would be beneficial for industrial applications. The combination of infrared thermography and supervised learning techniques provided the potential solution to this problem. This research investigates the application of machine learning techniques—artificial neural networks (ANNs) and support vector machines (SVMs)—in combination with thermography for cycle life estimation of lithium-ion polymer batteries. Infrared images were captured at 1 frame/min during 70 min of charging followed by 60 min of discharging for 410 cycles. The surface temperature profiles during either charging or discharging were used as the input nodes for ANN and SVM models. The results demonstrated that with thermal profiles as the input, ANN could estimate the current cycle life of studied cell with the error of < 10% under 10 min of testing time. While when compared to ANN, the accuracy of SVM-based forecast models was similar but generally required a longer amount of testing time.     

Quaternion attitude and disturbance observer mass estimation with low-cost sensors for industrial vehicles with trailers

Information about the vehicle mass and ground slope is important for many assistance functions in road and logistics vehicles. In intralogistics, safe speed limits for tractors depend on both slope and trailer mass.This work presents an estimation procedure for the attitude of a vehicle and the mass of a trailer attached to it. The estimator works in two steps. First, the attitude is estimated using an extended Kalman filter based on acceleration and angular rate measurements complemented by a single track vehicle model. In the second step, this information is used together with velocity and motor torque data to estimate the trailer mass and friction coefficient. A Kalman filter based disturbance observer for parameter estimation is compared to a recursive least squares identification. The mass estimation is extended by a structural break test to detect sudden mass changes when hitching and unhitching trailers.Multiple variants of the estimation scheme are implemented on an intralogistics vehicle. The performance of the proposed attitude and mass estimation solutions is demonstrated in comparison to state of the art reference algorithms in a large number of experiments. Compared to state of the art estimators, the proposed estimator yields a median 54 % reduction of pitch estimation RMSE and 40 % reduction of the mass estimation error. The structural break detection is able to detect all instances of hitching and unhitching of trailers with few false positives.     

A PAPR reduction technique using Hadamard transform combined with clipping and filtering based on DCT/IDCT for IM/DD optical OFDM systems

In Intensity Modulator/Direct Detection (IM/DD) optical OFDM systems, the high peak-to-power average ratio (PAPR) will cause signal impairments through the nonlinearity of modulator and fiber. In this paper, a joint PAPR reduction technique based on Hadamard transformation and clipping and filtering using DCT/IDCT transform has been proposed for mitigating the impairments in IM/DD optical OFDM system. We then experimentally evaluated the effect of PAPR reduction on the bit error rate (BER) performance and the results show the effectiveness of the proposed technique. At a bit error rate (BER) of 1 × 10⁻³, the receiver sensitivity of the proposed 2.5 Gb/s IM/DD optical OFDM system after 100-km standard single-mode fiber transmission has been improved by 0.8 dB, 1.3 dB and 3.1 dB for a launch power of 6.4 dBm, 8 dBm and 10 dBm respectively when compared with the classical system.     

Kinematic calibration of a 3-P(Pa)S parallel-type spindle head considering the thermal error

Calibration is considered to be the most effective way to improve the accuracy of parallel kinematic machine tools (PKMTs). However, ordinary calibrations only considered the time-invariant errors (manufacturing error), neglecting some time-variant errors, a significant one of which is thermal error. Therefore, in this paper, the influence of thermal error was considered in the calibration of a 3-P(Pa)S parallel-type spindle head. First, a new kinematic model of the spindle head was proposed, which is closer to the real physical model, so the thermal error of the spindle head can be considered in the model. Second, the structural parameters of the spindle head were expressed as the sum of the ideal parameters, the manufacturing errors, and the thermal errors. Third, the pose (position and orientation) of the end effector and the temperature of the spindle head were measured. The positions of the temperature sensors were selected using the global temperature sensitivity index (GTSI), which is derived from the global sensitivity index (GSI). Thus, by setting a standard temperature, the thermal error of the structural parameter can be obtained. Fourth, the influence of the thermal error was inputted into the identification equation for calibration, so the results are the structural parameters at the standard temperature (20 °C). To solve the ill-conditioning problem, a Regularization method was used in the identification. Finally, the calibration was verified on a 3-P(Pa)S-XY machine tool. The RTCP test, performed immediately after the measurement, shows that the maximum position error after the calibration is 0.019 mm at the tilt angle of 30° and 0.037 mm at 20°. In addition, the RTCP test after a temperature change shows that the calibration considering the thermal error can improve the average position accuracy from 0.025 mm to 0.015 mm. The calibration method in this paper is expected to be applicable for other machine tools.     

Ultra-thin flexible screen printed rechargeable polymer battery for wearable electronic applications

This research has demonstrated how an ultra-thin rechargeable battery technology has been fabricated using screen printing technology. The screen printing process enabled the sequential deposition of current collector, electrode and separator/electrolyte materials onto a polyethylene terephthalate (PET) substrate in order to form both flexible and rechargeable electrodes for a battery application. The anode and cathode fabricated were based on the conducting poly (3,4-ethylenedioxythiophen): poly (styrene sulfonate) (PEDOT: PSS) and polyethyleneimine (PEI) which were combined to form the electrodes. The difference in the oxidation level between the two electrodes produced an open circuit voltage of 0.60 V and displayed a practical specific capacity of 5.5 mAh g⁻¹. The battery developed had an active surface area of 400 mm² and a device thickness of 440 μm. The chemistry developed during this study displayed long-term cycling potential and proves the stability of the cells for continued usage. This technology has direct uses in future personal wearable electronic devices.     

Improved pilot-aided optical carrier phase recovery using average processing for pilot phase estimation

We propose and numerically investigate an improved pilot-aided (PA) optical carrier phase recovery (CPR) method using average processing for pilot phase estimation in order to suppress the amplified spontaneous emission (ASE) noise in PA coherent transmission systems. Extensive simulations for 28 Gbuad QPSK systems are implemented. The performance of proposed PA-CPR with averaging is comprehensively investigated and compared with PA-CPR without averaging and Viterbi & Viterbi phase estimation (VVPE). Results show that, PA-CPR with averaging can significantly improve the performance of PA-CPR without averaging, and the best averaging length in the average operation is determined by trading off between ASE noise and laser phase noise (PN). By comparing the optical-signal-to-noise-ratio (OSNR) penalties at bit error rate (BER) of 1 × 10^?3 using PA-CPR without averaging, PA-CPR with averaging and VVPE, the advantage of PA-CPR with averaging is further confirmed. Quantitatively, the tolerable linewidth-symbol-duration products (Δf · T) at 1-dB OSNR penalty by using PA-CPR without averaging, VVPE, and PA-CPR with averaging are 6 × 10^?5, 1.2 × 10^?4, and 5 × 10^?4, respectively.     

采用门控循环神经网络估计锂离子电池健康状态

锂离子电池健康状态（State of Health，SOH）描述了电池当前老化程度，对于提前对电池的故障及失控做出预警避免电池的不安全行为具有重要意义。其估计难点在于难以确定数量合适、相关性高的估计输入以及设计合适的估计算法。通过对现有电池老化数据集的研究发现，电池充电过程中电压曲线数据相对稳定，且随着电池的老化出现规律性变化。因此，文中直接采用充电过程中电压数据作为估计SOH的输入，并在数据驱动的框架下，提出了一种基于门控循环神经网络（Recurrent Neural Networks with Gated Recurrent Unit, GRU-RNN）的锂电池SOH估计方法。该方法能够挖掘出一维电压数据中的时序特征和SOH之间的映射规律。在两个公开的电池老化数据集上的实验结果表明，提出的方法达到了1.25%的均方绝对误差和低于5.62%的最大误差，在估计精度上达到现有技术发展水平。     

Fuzzy quantization based bit transform for low bit-resolution motion estimation

This study proposes a novel fuzzy quantization based bit transform for low bit-resolution motion estimation. We formalize the procedure of bit resolution reduction by two successive steps, namely interval partitioning and interval mapping. The former is a many-to-one mapping which determines motion estimation performance, while the latter is a one-to-one mapping. To gain a reasonable interval partitioning, we propose a non-uniform quantization method to compute coarse thresholds. They are then refined by using a membership function to solve the mismatch of pixel values near threshold caused by camera noise, coding distortion, etc. Afterwards, we discuss that the sum of absolute difference (SAD) is one of the fast matching metrics suitable for low bit-resolution motion estimation in the sense of mean squared errors. A fuzzy quantization based low bit-resolution motion estimation algorithm is consequently proposed. Our algorithm not only can be directly employed in video codecs, but also be applied to other fast or complexity scalable motion estimation algorithms. Extensive experimental results show that the proposed algorithm can always achieve good motion estimation performances for video sequences with various characteristics. Compared with one-bit transform, multi-thresholding two-bit transform, and adaptive quantization based two-bit transform, our bit transform separately gains 0.98 dB, 0.42 dB, and 0.24 dB improvement in terms of average peak signal-to-noise ratio, with less computational cost as well.     

Improved macroblock level rate control for the spatially scalable extension of H.264/AVC

An improved rate control algorithm, designed for scalable video coders incorporating interlayer prediction, is proposed. Firstly, a Rate Distortion (RD) model for interlayer prediction involving the spatial enhancement layers is devised. An optimised Mean Absolute Difference (MAD) prediction model for the spatial enhancement layers that considers both the MAD from the spatial base layer in the same frame and the MAD from the corresponding macroblock in previous frames is also proposed. Simulation results show that the resulting algorithm produces accurate rate control with an average bit rate error of less than 0.26%. Compared with the JVT-W043 default rate control algorithm of the JSVM, the proposed algorithm improves the average PSNR by up to 0.53 dB or reduces the bit rate by an average of 10.95%. Furthermore, the proposed algorithm can be combined with the existing rate control scheme for H.264/AVC, resulting in further improvements.     

Correlation based universal image/video coding loss recovery

Coding artifacts are annoying in highly compressed signals. Most of the existing artifact reduction methods are designed for one specific type of artifacts, codecs, and bitrates, which are complex and exclusive for one type of artifact reduction. Since both the compressed image/video and the coding error contain information of the original signal, they are highly correlated. Therefore, we try to recover some lost data based on the correlation between the compressed signal and the coding error, and introduce a novel and universal artifact reduction method. Firstly, according to the spatial correlation among pixels, a pixel-adaptive anisotropic filter is designed to reconstruct the distorted signal. Next, a globally optimal filter is designed to further recover the coding loss. Experimental results demonstrate that within an extensive range of bitrates, the proposed method achieves about 0.8 dB, 0.45 dB, 0.3 dB, and 0.2 dB on average of PSNR improvement for JPEG, MPEG4, H.264/AVC, and HEVC compressed signals, respectively.     

New Battery Model and State-of-Health Determination Through Subspace Parameter Estimation and State-Observer Techniques

This paper describes a novel adaptive battery model based on a remapped variant of the well-known Randles' lead-acid model. Remapping of the model is shown to allow improved modeling capabilities and accurate estimates of dynamic circuit parameters when used with subspace parameter-estimation techniques. The performance of the proposed methodology is demonstrated by application to batteries for an all-electric personal rapid transit vehicle from the urban light transport (ULTRA) program, which is designated for use at Heathrow Airport, U.K. The advantages of the proposed model over the Randles' circuit are demonstrated by comparisons with alternative observer/estimator techniques, such as the basic Utkin observer and the Kalman estimator. These techniques correctly identify and converge on voltages associated with the battery state-of-charge (SoC), despite erroneous initial conditions, thereby overcoming problems attributed to SoC drift (incurred by Coulomb-counting methods due to overcharging or ambient temperature fluctuations). Observation of these voltages, as well as online monitoring of the degradation of the estimated dynamic model parameters, allows battery aging (state-of-health) to also be assessed and, thereby, cell failure to be predicted. Due to the adaptive nature of the proposed algorithms, the techniques are suitable for applications over a wide range of operating environments, including large ambient temperature variations. Moreover, alternative battery topologies may also be accommodated by the automatic adjustment of the underlying state-space models used in both the parameter-estimation and observer/estimator stages.     

No-reference analysis of decoded MPEG images for PSNR estimation and post-processing

We propose no-reference analysis and processing of DCT (Discrete Cosine Transform) coded images based on estimation of selected MPEG parameters from the decoded video. The goal is to assess MPEG video quality and perform post-processing without access to neither the original stream nor the code stream. Solutions are presented for MPEG-2 video. A method to estimate the quantization parameters of DCT coded images and MPEG I-frames at the macro-block level is presented. The results of this analysis is used for deblocking and deringing artifact reduction and no-reference PSNR estimation without code stream access. An adaptive deringing method using texture classification is presented. On the test set, the quantization parameters in MPEG-2 I-frames are estimated with an overall accuracy of 99.9% and the PSNR is estimated with an overall average error of 0.3 dB. The deringing and deblocking algorithms yield improvements of 0.3 dB on the MPEG-2 decoded test sequences.