Single event effects evaluation on convolution neural network in Xilinx 28 nm system on chip

Convolutional neural networks(CNNs) exhibit excellent performance in the areas of image recognition and object detection, which can enhance the intelligence level of spacecraft. However, in aerospace, energetic particles, such as heavy ions, protons, and alpha particles, can induce single event effects(SEEs) that lead CNNs to malfunction and can significantly impact the reliability of a CNN system. In this paper, the MNIST CNN system was constructed based on a 28 nm systemon-chip(SoC), and then an alpha particle irradiation experiment and fault injection were applied to evaluate the SEE of the CNN system. Various types of soft errors in the CNN system have been detected, and the SEE cross sections have been calculated. Furthermore, the mechanisms behind some soft errors have been explained. This research will provide technical support for the design of radiation-resistant artificial intelligence chips.

Straw return increases crop production by improving soil organic carbon sequestration and soil aggregation in a long-term wheat-cotton cropping system

Straw return is a promising strategy for managing soil organic carbon(SOC)and improving yield stability.However,the optimal straw return strategy for sustainable crop production in the wheat(Triticum aestivum L.)-cotton(Gossypium hirsutum L.)cropping system remains uncertain.The objective of this study was to quantify the long-term(10 years)impact of carbon(C)input on SOC sequestration,soil aggregation and crop yields in a wheat-cotton cropping system in the Yangtze River Valley,China.Five treatments were arranged with a single-factor randomized design as follows:no straw return(Control),return of wheat straw only(Wt),return of cotton straw only(Ct),return of 50%wheat and 50%cotton straw(Wh-Ch)and return of 100%wheat and 100%cotton straw(Wt-Ct).In comparison to the Control,the SOC content increased by 8.4 to 20.2%under straw return.A significant linear positive correlation between SOC sequestration and C input(1.42-7.19 Mg ha^(−1)yr^(−1))(P<0.05)was detected.The percentages of aggregates of sizes>2 and 1-2 mm at the 0-20 cm soil depth were also significantly elevated under straw return,with the greatest increase of the aggregate stability in the Wt-Ct treatment(28.1%).The average wheat yields increased by 12.4-36.0%and cotton yields increased by 29.4-73.7%,and significantly linear positive correlations were also detected between C input and the yields of wheat and cotton.The average sustainable yield index(SYI)reached a maximum value of 0.69 when the C input was 7.08 Mg ha^(−1)yr^(−1),which was close to the maximum value(SYI of 0.69,C input of 7.19 Mg ha^(−1)yr^(-1))in the Wt-Ct treatment.Overall,the return of both wheat and cotton straw was the best strategy for improving SOC sequestration,soil aggregation,yields and their sustainability in the wheat-cotton rotation system.

Simulation and fabrication of in vitro microfluidic microelectrode array chip for patterned culture and electrophysiological detection of neurons

To enable the detection and modulation of modularized neural networks in vitro,this study proposes a microfluidic microelectrode array chip for the cultivation,compartmentalization,and control of neural cells.The chip was designed based on the specific structure of neurons and the requirements for detection and modulation.Finite-element analysis of the chip’s flow field was conducted using the COMSOL Multiphysics software,and the simulation results show that the liquid within the chip can flow smoothly,ensuring stable flow fields that facilitate the uniform growth of neurons within the microfluidic channels.By employing MEMS technology in combination with nanomaterial modification techniques,the microfluidic microelectrode array chip was fabricated successfully.Primary hippocampal neurons were cultured on the chip,forming a well-defined neural network.Spontaneous electrical activity of the detected neurons was recorded,exhibiting a 23.7%increase in amplitude compared to neuronal discharges detected on an open-field microelectrode array.This study provides a platform for the precise detection and modulation of patterned neuronal growth in vitro,potentially serving as a novel tool in neuroscience research.

On-chip quantum NOON state sensing for temperature and humidity

A maximal photon number entangled state,namely NOON state,can be adopted for sensing with a quantum enhancedprecision.In this work,we designed silicon quantum photonic chips containing two types of Mach-Zehnder interferometerswherein the two-photon NOON state,sensing element for temperature or humidity,is generated.Compared with classicallight or single photon case,two-photon NOON state sensing shows a solid enhancement in the sensing resolution andprecision.As the first demonstration of on-chip quantum photonic sensing,it reveals the advantages of photonic chips forhigh integration density,small-size,stability for multiple-parameter sensing serviceability.A higher sensing precision isexpected to beat the standard quantum limit with a higher photon number NOON state.

Simplified quantitative analysis method and its application in the insitu synthesized copper-based azide chips

Copper-based azide(Cu(N_(3))2 or CuN_(3),CA)chips synthesized by in-situ azide reaction and utilized in miniaturized explosive systems has become a hot research topic in recent years.However,the advantages of in-situ synthesis method,including small size and low dosage,bring about difficulties in quantitative analysis and differences in ignition capabilities of CA chips.The aim of present work is to develop a simplified quantitative analysis method for accurate and safe analysis of components in CA chips to evaluate and investigate the corresponding ignition ability.In this work,Cu(N_(3))2 and CuN_(3)components in CA chips were separated through dissolution and distillation by utilizing the difference in solubility and corresponding content was obtained by measuring N_(3)-concentration through spectrophotometry.The spectrophotometry method was optimized by studying influencing factors and the recovery rate of different separation methods was studied,ensuring the accuracy and reproducibility of test results.The optimized method is linear in range from 1.0-25.0 mg/L,with a correlation coefficient R^(2)=0.9998,which meets the requirements of CA chips with a milligram-level content test.Compared with the existing ICP method,component analysis results of CA chips obtained by spectrophotometry are closer to real component content in samples and have satisfactory accuracy.Moreover,as its application in miniaturized explosive systems,the ignition ability of CA chips with different component contents for direct ink writing CL-20 and the corresponding mechanism was studied.This study provided a basis and idea for the design and performance evaluation of CA chips in miniaturized explosive systems.

A novel integrated microfluidic chip for on-demand electrostatic droplet charging and sorting

On-demand droplet sorting is extensively applied for the efficient manipulation and genome-wide analysis of individual cells.However,state-of-the-art microfluidic chips for droplet sorting still suffer from low sorting speeds,sample loss,and labor-intensive preparation procedures.Here,we demonstrate the development of a novel microfluidic chip that integrates droplet generation,on-demand electrostatic droplet charging,and high-throughput sorting.The charging electrode is a copper wire buried above the nozzle of the microchannel,and the deflecting electrode is the phosphate buffered saline in the microchannel,which greatly simplifies the structure and fabrication process of the chip.Moreover,this chip is capable of high-frequency droplet generation and sorting,with a frequency of 11.757 kHz in the drop state.The chip completes the selective charging process via electrostatic induction during droplet generation.On-demand charged microdroplets can arbitrarilymove to specific exit channels in a three-dimensional(3D)-deflected electric field,which can be controlled according to user requirements,and the flux of droplet deflection is thereby significantly enhanced.Furthermore,a lossless modification strategy is presented to improve the accuracy of droplet deflection or harvest rate from 97.49% to 99.38% by monitoring the frequency of droplet generation in real time and feeding it back to the charging signal.This chip has great potential for quantitative processing and analysis of single cells for elucidating cell-to-cell variations.

Integrated strategy for real-time wind power fluctuation mitigation and energy storage system control

To address the impact of wind-power fluctuations on the stability of power systems,we propose a comprehensive approach that integrates multiple strategies and methods to enhance the efficiency and reliability of a system.First,we employ a strategy that restricts long-and short-term power output deviations to smoothen wind power fluctuations in real time.Second,we adopt the sliding window instantaneous complete ensemble empirical mode decomposition with adaptive noise(SW-ICEEMDAN)strategy to achieve real-time decomposition of the energy storage power,facilitating internal power distribution within the hybrid energy storage system.Finally,we introduce a rule-based multi-fuzzy control strategy for the secondary adjustment of the initial power allocation commands for different energy storage components.Through simulation validation,we demonstrate that the proposed comprehensive control strategy can smoothen wind power fluctuations in real time and decompose energy storage power.Compared with traditional empirical mode decomposition(EMD),ensemble empirical mode decomposition(EEMD),and complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN)decomposition strategies,the configuration of the energy storage system under the SW-ICEEMDAN control strategy is more optimal.Additionally,the state-of-charge of energy storage components fluctuates within a reasonable range,enhancing the stability of the power system and ensuring the secure operation of the energy storage system.

Rapid fabrication of modular 3D paper-basedmicrofluidic chips using projection-based 3D printing

Paper-based microchips have different advantages,such as better biocompatibility,simple production,and easy handling,making them promising candidates for clinical diagnosis and other fields.This study describes amethod developed to fabricate modular three-dimensional(3D)paper-based microfluidic chips based on projection-based 3D printing(PBP)technology.A series of two-dimensional(2D)paper-based microfluidic modules was designed and fabricated.After evaluating the effect of exposure time on the accuracy of the flow channel,the resolution of this channel was experimentally analyzed.Furthermore,several 3D paper-based microfluidic chips were assembled based on the 2D ones using different methods,with good channel connectivity.Scaffold-based 2D and hydrogel-based 3D cell culture systems based on 3D paper-based microfluidic chips were verified to be feasible.Furthermore,by combining extrusion 3D bioprinting technology and the proposed 3D paper-based microfluidic chips,multiorgan microfluidic chips were established by directly printing 3D hydrogel structures on 3D paperbased microfluidic chips,confirming that the prepared modular 3D paper-based microfluidic chip is potentially applicable in various biomedical applications.

Efficient stochastic parallel gradient descent training for on-chip optical processor

In recent years,space-division multiplexing(SDM)technology,which involves transmitting data information on multiple parallel channels for efficient capacity scaling,has been widely used in fiber and free-space optical communication sys-tems.To enable flexible data management and cope with the mixing between different channels,the integrated reconfig-urable optical processor is used for optical switching and mitigating the channel crosstalk.However,efficient online train-ing becomes intricate and challenging,particularly when dealing with a significant number of channels.Here we use the stochastic parallel gradient descent(SPGD)algorithm to configure the integrated optical processor,which has less com-putation than the traditional gradient descent(GD)algorithm.We design and fabricate a 6×6 on-chip optical processor on silicon platform to implement optical switching and descrambling assisted by the online training with the SPDG algorithm.Moreover,we apply the on-chip processor configured by the SPGD algorithm to optical communications for optical switching and efficiently mitigating the channel crosstalk in SDM systems.In comparison with the traditional GD al-gorithm,it is found that the SPGD algorithm features better performance especially when the scale of matrix is large,which means it has the potential to optimize large-scale optical matrix computation acceleration chips.

Effects of Using Softwood Pellet Biochar Prepared at Different Temperatures with Grass Chippings on Retention of Heavy Metals in Contaminated Soils

Heavy metals have been viewed as hazardous environmental pollutants, and anthropogenic activities due to their high toxicity and persistent nature in the environment. Anthropogenic activities such as artisanal mining, industrial activities, improper usage of fertilizers and pesticides, and indiscriminate open waste disposal bring about an increase in the presence of heavy metals in the environment. In the Keffi Metropolis, different elements lead to land contamination which debilitates soil quality, plant survival, human well-being, and the environment as a result of extensive dispersion or quantity of heavy metals in the soil and water. In recent years, biochar has emerged as a promising soil amendment for mitigating heavy metal pollution due to its unique physicochemical properties. This paper provides the effects of softwood pellet biochar on the retention of heavy metals in contaminated soils. A microcosm experiment was carried out to investigate the effects of biochar on the retention of heavy metals in contaminated soils. This research aimed to give an overview of the effects of softwood biochar at different temperatures (550˚C and 700˚C) on the retention of heavy metals and metalloids released from the soil during water inundation. The results show that the addition of organic matter (grass chippings) minimizes heavy metal mobilization. Also, biochar at high temperatures is more effective than those at low temperatures. The expected outcome of the research analysis includes providing insights into the role of biochar in retaining heavy metal contamination and further understanding the use of biochar as a sorbent for the management of contaminated soil.

An electrochemiluminescent magneto-immunosensor for ultrasensitive detection of hs-cTnI on a microfluidic chip

Sensitive detection and precise quantitation of trace-level crucial biomarkers in a complex sample matrix has become an important area of research.For example,the detection of high-sensitivity cardiac troponin I (hs-cTnI) is strongly recommended in clinical guidelines for early diagnosis of acute myocardial infarction.Based on the use of an electrode modified by single-walled carbon nanotubes (SWCNTs) and a Ru(bpy)32+-doped silica nanoparticle (Ru@SiO2)/tripropylamine (TPA) system,a novel type of electrochemiluminescent (ECL) magnetoimmunosensor is developed for ultrasensitive detection of hs-cTnI.In this approach,a large amount of[Ru(bpy)3]2+is loaded in SiO2(silica nanoparticles) as luminophores with high luminescent efficiency and SWCNTs as electrode surface modification material with excellent electrooxidation ability for TPA.Subsequently,a hierarchical micropillar array of microstructures is fabricated with a magnet placed at each end to efficiently confine a single layer of immunomagnetic microbeads on the surface of the electrode and enable 7.5-fold signal enhancement In particular,the use of transparent SWCNTs to modify a transparent ITO electrode provides a two-order-of-magnitude ECL signal amplification.A good linear calibration curve is developed for hs-cTnI concentrations over a wide range from 10 fg/ml to 10 ng/ml,with the limit of detection calculated as 8.720 fg/ml (S/N=3).This ultrasensitive immunosensor exhibits superior detection performance with remarkable stability,reproducibility,and selectivity.Satisfactory recoveries are obtained in the detection of hs-cTnI in human serum,providing a potentia analysis protocol for clinical applications.

Exploring the mechanism of electroacupuncture at different acupoints on acute colitis rats based on JAK2/STAT3/SOCS1 signaling pathway

Objective:To investigate the mechanism of JAK2/STAT3/SOCS1 signaling pathway in electroacupuncture of different acupoints on acute colitis rats.Methods:36 SPF SD rats were randomly divided into 6 groups,with 6 rats in each group.The rat model of acute colitis was prepared by enema with glacial acetic acid solution.After the model was established,electroacupuncture was given to each acupoint group,with density wave,frequency 2Hz-50 Hz,intensity 2 mA,muscle tremor as the degree 20 min/time,1 time/day,for 3 consecutive days.Observe the general condition of rats;the pathological changes of colonic mucosa in rats were observed by HE method.The contents of serum interleukin-4(IL-4)and interleukin-8(IL-8)were detected by ELISA.Western blot and RT-PCR were used to detect the expression of JAK2,STAT3,SOCS1 protein and mRNA in rat colon tissue.Results:In contrast to the normal group,the overall condition of the model group was worse,the colonic mucosa was severely damaged,even necrotic,and the ulcer surface was obvious.The content of IL-4 in serum was obviously reduced,and the content of IL-8 was obviously go up(P<0.01).The protein content of JAK2,STAT3 and the expression of JAK2,STAT3 mRNA in colon tissue of rats were obviously go up,while the protein content of SOCS1 and the expression of SOCS1 mRNA were obviously reduced(P<0.01).In contrast to the model group,the general condition of rats in each acupoint group was significantly improved,the damage and necrosis of colonic mucosa and ulcer surface were obviously alleviated,the content of IL-4 in serum was obviously go up,and the content of IL-8 was significantly decreased(P<0.01).The protein content of JAK2,STAT3 and the expression of JAK2,STAT3 mRNA in colon tissue of rats were obviously reduced,while the protein content of SOCS1 and the expression of SOCS1 mRNA were obviously go up(P<0.05,P<0.01).Comparison of different acupoint groups,the colonic mucosal injury in the Zusanli group was significantly reduced,the content of serum IL-4 was significantly increased,and the content of IL-8 was significantly decreased(P<0.05,P<0.01).The protein content and mRNA expression of JAK2 and STAT3 in colon tissue were significantly down-regulated,while the protein content and mRNA expression of SOCS1 were significantly go up(P<0.05,P<0.01).Conclusion:Electroacupuncture at each acupoint can improve the damage of colonic mucosa and reduce the inflammatory response.The therapeutic effect of Zusanli(ST36)is better than that of Tianshu(ST25),Dachangshu(BL25)and Shangjuxu(ST37).The mechanism may be related to the regulation of JAK2/STAT3/SOCS1 signaling pathway related proteins and inflammatory cytokines IL-4 and IL-8.

Analysis of the Tragedy of Vila Socóin Cubatão (São Paulo, Brazil) Using the Haddon Matrix: A Comprehensive Examination of Socio-Environmental Factors and Risk Mitigation Strategies

The tragedy of Vila Socó epitomizes the socio-environmental repercussions of rapid industrialization in Cubatão. Beginning in the 1940s with the construction of the Anchieta highway, the city experienced an influx of migrants drawn by burgeoning industries, leading to unplanned urban growth and the emergence of vulnerable communities like Vila Socó. This article examines the interconnected factors—such as demographic shifts, inadequate planning, and regulatory oversight—that culminated in the devastating fire of 1984, claiming numerous lives and highlighting systemic failures. Utilizing the Haddon Matrix, this study dissects the Vila Socó incident, emphasizing the roles of human error, infrastructure integrity, and socio-economic disparities in disaster causation. By contextualizing the tragedy within Cubatão’s industrial trajectory, it underscores the urgent need for comprehensive risk assessment and proactive mitigation strategies in rapidly developing regions globally. Beyond its immediate focus, this work offers broader insights into the dynamics of industrial disasters and their socio-economic implications. As pipelines continue to play a vital role in global energy infrastructure, the lessons drawn from Vila Socó’s tragedy resonate deeply, emphasizing the imperative of robust safety protocols and accountable governance to prevent similar catastrophes in the future.

Review on the Usage of Synchronous and Asynchronous FIFOs in Digital Systems Design

First-Input-First-Output (FIFO) buffers are extensively used in contemporary digital processors and System-on-Chips (SoC). There are synchronous FIFOs and asycnrhonous FIFOs. And different sized FIFOs should be implemented in different ways. FIFOs are used not only for the pipeline design within a processor, for the inter-processor communication networks, for example Network-on-Chips (NoCs), but also for the peripherals and the clock domain crossing at the whole SoC level. In this paper, we review the interface, the circuit implementation, and the various usages of FIFOs in various levels of the digital design. We can find that the usage of FIFOs could greatly facilitate the signal storage, signal decoupling, signal transfer, power domain separation and power domain crossing in digital systems. We hope that more attentions are paid to the usages of synchronous and asynchronous FIFOs and more sophististicated usages are discovered by the digital design communities.

基于CSO-AUKF的锂电池SOC估算方法

电池荷电状态(SOC)估算是电池管理系统(BMS)的关键技术之一。针对锂电池提出了一种基于猫群(CSO)算法和自适应无迹卡尔曼滤波(AUKF)算法相结合的电池SOC估算方法;建立了基于二阶RC等效电路模型的锂电池状态方程,采用CSO算法提高电池辨识精度,联合AUKF算法对SOC进行估算;基于混合脉冲功率测试工况(HPPC)和间歇恒流放电工况下的数据对该方法有效性进行了验证。研究结果表明:基于CSO-AUKF估算,SOC最大误差小于1.64%,估算精度及稳定性均好于遗传算法。

引入PID反馈的SHAEKF算法估算电池SOC

电池荷电状态(SOC)的估算精度是电动汽车电池组的重要指标。为提升SOC估算精度,在融合Sage-Husa扩展卡尔曼滤波(SHEKF)算法与自适应扩展卡尔曼滤波(AEKF)算法的基础上,增加比例积分微分(PID)反馈环节,形成改进算法。采用粒子群优化(PSO)算法对二阶RC等效电路模型进行参数辨识;用开源电池数据集对模型和算法进行实验和分析。改进的SHAEKF算法在电池动态应力测试(DST)、北京动态应力测试(BJDST)和美国联邦城市驾驶(FUDS)等工况下的平均估计误差都在1%以内,与单纯的融合算法SHAEKF算法相比,最大误差可减小5%。

穿石通痹汤通过调节GABRB1-SOCS1/JAK1/STAT3信号途径对CIA模型大鼠关节炎症损伤的影响

目的 探讨穿石通痹汤对胶原诱导性关节炎(Collagen II induced arthritis,CIA)模型大鼠关节滑膜免疫炎性损伤的疗效及作用机制。方法 SPF级雄性SD大鼠,体质量(200±10)g,采用大鼠尾根部注射牛CⅡ方法制备CIA模型,将成模大鼠按随机数字表法分为模型组、阳性药组、穿石通痹汤组,每组各6只,另取6只未造模大鼠作为正常组。正常组与模型组隔日予去离子水10 ml/kg灌胃,阳性药组予甲氨蝶呤注射液每周0.5 mg/kg腹腔注射,穿石通痹汤组按生药量11.2 g/kg隔日灌胃给药,连续干预4周后处死大鼠,采集血浆、膝关节滑膜及踝关节标本。以HE染色观察大鼠踝关节病理变化;采用Westernblot检测大鼠膝关节滑膜pJAK1、JAK1、p38、GABRB1的蛋白表达水平;ELISA检测血浆IL-6,STAT3,SOCS1表达水平;并采用UHPLC-Q-Exactive Orbitrap MS分析血浆代谢物成分。结果 与正常组比较,模型组大鼠踝关节滑膜明显增生、严重骨质破坏以及炎性细胞浸润;与模型组比较,穿石通痹汤组大鼠关节骨质破坏、关节病变整体评分明显改善。与正常组比较,模型组GABRB1、SOCS1蛋白表达水平显著降低(P<0.01),p38、pJAK1、IL-6,STAT3蛋白表达水平明显升高(P<0.01,P<0.05);与模型组比较,穿石通痹汤组及阳性药组GABRB1、SOCS1蛋白表达水平均显著上调(P<0.01,P<0.05),并明显抑制p38、pJAK1、IL-6,STAT3的蛋白表达(P<0.01),且穿石通痹汤组对GABRB1的上调作用及pJAK1抑制作用显著优于阳性药组(P<0.01);血浆代谢物分析发现甘油磷脂代谢、花生四烯酸代谢、鞘脂代谢等代谢途径及其中50个代谢产物与本病发生密切相关。结论 穿石通痹汤能有效改善CIA模型大鼠关节滑膜免疫炎性代谢性损伤,其机制可能与调节GABRB1-SOCS1/JAK1/STAT3信号途径,调控脂质代谢途径相关。

壳寡糖通过调控SOCS3/STAT3信号通路改善脂多糖诱导的小鼠神经炎症

目的探讨壳寡糖(chitosan oligosaccharide,COS)对脂多糖(lipopolysaccharide,LPS)诱导小鼠神经炎症的改善作用及机制。方法通过对10周龄C57BL/6N小鼠腹腔注射LPS建立神经炎症模型。动物随机分为5组,分别是:对照(CON)组、LPS组、LPS+COS低剂量(LPS+COS 50 mg/kg)组、LPS+COS中剂量(LPS+COS 100 mg/kg)组、LPS+COS高剂量(LPS+COS 200 mg/kg)组。LPS注射完毕后进行旷场实验、新物体识别、Morris水迷宫等行为学实验。处死动物后,收集脑组织,酶联免疫吸附实验(enzyme linked immunosorbent assay,ELISA)分析脑内促炎因子白细胞介素-2(interleukin-2,IL-2)、白细胞介素-6(interleukin-6,IL-6)和抗炎因子白细胞介素-4(interleukin-4,IL-4)的表达;Western blot分析脑内信号传导及转录激活蛋白(STAT3)、细胞因子信号抑制物(SOCS3)蛋白的表达水平。结果行为学实验结果表明,COS可以改善LPS诱发的小鼠认知障碍下降等表现。ELISA结果表明,LPS组小鼠的促炎细胞因子的释放量显著增加,抗炎细胞因子的释放量显著降低;而COS灌胃可逆转这一变化趋势。Western blot结果提示,与CON组相比,LPS的STAT3磷酸化水平显著升高,同时也促进SOCS3的蛋白表达升高;而COS则显著下调这两个蛋白的表达。结论COS可能通过抑制SOCS3/STAT3信号通路改善LPS引起的小鼠神经炎症。

不同温度下的基于BPNN-AUKF的新型自动水下航行器SOC估计器

本研究提出了一种基于反向传播神经网络(BPNN)和自适应无迹卡尔曼滤波器(AUKF)的SOC(state of charge)估计方法。首先针对电池SOC与端电压之间在不同温度下的关系,研究设计了一系列温度补偿策略,以提高在低温、低SOC条件下的估计精度。其次,利用反向传播神经网络(BPNN)建立了一个耦合了温度补偿策略的电池模型。这个模型能更好地适应低温和低SOC条件下的电池状态变化,提高了SOC估计的准确性。最后,基于BPNN电池模型建立了BPNN-AUKF的SOC估计框架,通过利用测量值与测量预测值之间的信息和残差序列,对系统过程和测量噪声协方差进行估计修正。通过实验验证,发现该方法在低温环境下具有明显优势,相比传统方法能够更准确地估计电池的SOC,且具备较好的泛化能力。这种基于BPNN-AUKF方法的SOC估计器不仅适用于自主无人潜水器(AUV),而且对于其他在复杂环境中工作的车辆也具有广泛的应用价值。

基于AR-ECM平均差异模型的串联电池组SOC、容量多尺度联合估计方法

考虑电池单体老化差异所致的电池组不一致性,针对串联电池组荷电状态(state of charge,SOC)、容量估计问题,提出一种基于自回归等效电路模型(autoregression equivalent circuit model,AR-ECM)的平均差异模型(mean-difference model,MDM)。基于此模型,提出串联电池组SOC、容量多尺度联合估计算法。该算法由2个部分组成,一是基于AR-ECM的MDM及差异化模型参数辨识策略:条件辨识策略和定频分组辨识策略;二是基于多时间尺度H无穷滤波(multi-timescale H infinity filter,Mts-HIF)的电池组SOC、容量联合估计算法。通过将所提出MDM中的自回归平均模型(autoregression mean model,AR-MM)与传统MDM中的n阶RC平均模型(nRC mean model,nRC-MM)比较,结果表明所提出的AR-MM在复杂运行工况下具有更优的动态跟随性能。依据最小化信息量准则(akaike information criterion,AIC),AR-MM具有更优的复杂度与精度的权衡。通过与基于多时间尺度扩展卡尔曼滤波(multi-timescale extended Kalman filter,Mts-EKF)联合状态估计算法比较,结果表明所提出的Mts-HIF状态估计算法具有更优的鲁棒性、精度和收敛速度。