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State-of-charge estimation for Lithium-Ion batteries using Kalman filters based on fractional-order models

CONNECTION SCIENCE 2022年第1期34卷 162-184页

作者： Xing, Likun Ling, Liuyi Gong, Bing Zhang, Menglong Anhui Univ Sci & Technol Sch Elect & Informat Technol Huainan 232001 Peoples R China Anhui Univ Sci & Technol Sch Artificial Intelligence Huainan 232001 Peoples R China

The accuracy of state of charge estimation results will directly affect the performance of battery management system. Due to such, we focus in this article on the SOC estimation of Lithium-Ion batteries based on a fractional second-order RC model with free noninteger differentiation orders. For such an estimation, three Kalman filters are employed: the adaptive extended Kalman filter (AEKF), extended Kalman filter (EKF), and Unscented Kalman Filter (UKF). The Fractional-Order Model (FOM) parameters and differentiation orders are identified by the particle swarm Optimization (PSO) algorithm, and a pulsed-discharge test is implemented to verify the accuracy of parameter identification. The output voltage error of the FOM model is much less than that of the Integer-Order Model (IOM). The FOM model has lower root-mean square error (RMSE), the mean absolute error (MAE), and the maximum absolute error (MAXAE) of SOC estimation than the IOM model during the SOC estimation regardless of AEKF, EKF or UKF. Experimental results show that the FOM can simulate the polarisation on effect and charge-discharge characteristics of the battery more realistically, demonstrating that the SOC estimation based on FOM is more accurate and promising than the one based on the IOM when using the same Kalman filters.

关键词： Fractional calculus Lithium-Ion batteries state-of-charge particle swarm optimisation algorithm Kalman filter

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Robust calibration method for distributed ISAR time-varying frequency errors based on the contrast maximisation principle

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IET RADAR SONAR AND NAVIGATION 2020年第7期14卷 1068-1078页

作者： Kang, Hailong Li, Jun Zhang, Zijing Ma, Hui Li, Han Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Peoples R China

The linear time-varying frequency errors (LTFE) caused by the mismatch of transmitter and receiver oscillators can defocus the imaging result of distributed inverse synthetic aperture radar (ISAR) seriously. The LTFE calibration method based on the entropy minimization principle is sensitive to signal-to-noise ratio (SNR), and its performance is degraded significantly under low SNR conditions. In addition, this method uses enumeration algorithm to solve the optimization problem, which has a heavy computation burden. Therefore, a robust calibration method based on the contrast maximization principle is proposed. Compared with image entropy, image contrast has better anti-noise ability because it has better sensitivity property, namely, the change of image contrast is sharper than the change of image entropy. In the proposed method, the estimation of frequency error coefficient is modelled as an unconstrained optimization problem with image contrast as cost function, and the particle swarm optimization (PSO) algorithm is used to search the global optimal solution. Then, the LTFE can be calibrated by the estimated frequency error coefficient. The proposed method has better robustness, which can work well under low SNR conditions. Besides, it has higher computational efficiency. Simulations are carried out to verify the effectiveness and robustness of the proposed method.

关键词： radar imaging synthetic aperture radar entropy minimisation optimisation calibration particle swarm optimisation robust calibration method distributed ISAR time-varying frequency errors contrast maximisation principle linear time-varying frequency errors transmitter receiver oscillators imaging result distributed inverse synthetic aperture radar LTFE calibration method entropy minimisation principle signal-to-noise ratio low SNR conditions heavy computation burden distributed ISAR LTFE image entropy image contrast anti-noise ability unconstrained optimisation problem particle swarm optimisation algorithm estimated frequency error coefficient

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Declining multi inverter-based total harmonic distortion with the aid of hybrid optimisation technique

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IET SCIENCE MEASUREMENT & TECHNOLOGY 2015年第3期9卷 285-293页

作者： Sathyanarayanan, Bharath Vaniyambadi Mani, Gopinath Bharath Univ Dept EEE Chennai Tamil Nadu India Dr NGP Inst Technol Dept EEE Coimbatore Tamil Nadu India

Multilevel inverter has arrived on the scene as an attractive and unique tool which is extensively employed for adapting dc (direct current) voltage to ac (alternating current) voltage. These appliances have recently taken shape as reliable sources of elevated power and found themselves well-utilised more often than not in industrial applications, by employing sine or adapted sine waves. The sine wave form generated in the multilevel inverter output has huge harmonics which should be minimised by appropriate steps. With a view to minimise the harmonics at the output signal, it is necessary to cut short the related total harmonic deformation (THD) of switching angles. Genetic algorithm is widely employed for the function of harmonic optimisation. However a hurdle appears as the cost function tends to invite further intricacy for the optimisation, entailing an added number of iterations. Therefore, with an eye on scaling down the number of iterations, the intention of genetic and particle swarm optimisation algorithms is to optimise the switching angles to the utmost. This method also leads to the decline of the related THD values. The innovative method is executed in the MATLAB/Simulink working platform.

关键词： harmonic distortion particle swarm optimisation genetic algorithms invertors waveform generators power semiconductor switches switching convertors iterative methods multilevel inverter-based total harmonic distortion declination hybrid optimisation technique elevated power sine waves IGBT switches switching function solitary converter semiconductor power converter harmonics minimisation total harmonic deformation genetic algorithm harmonic optimisation iteration method particle swarm optimisation algorithm switching angle optimisation THD Matlab Simulink

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An optimisation approach for uncertainty-based long-term production scheduling in open-pit mines using meta-heuristic algorithms

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INTERNATIONAL JOURNAL OF MINING RECLAMATION AND ENVIRONMENT 2021年第2期35卷 115-140页

作者： Tolouei, Kamyar Moosavi, Ehsan Tabrizi, Amir Hossein Bangian Afzal, Peyman Bazzazi, Abbas Aghajani Islamic Azad Univ South Tehran Branch Dept Petr & Min Engn Tehran Iran Univ Kashan Dept Min Engn Kashan Iran

In mines planning, the long-term production scheduling problem (LTPSP) in open-pit mines is considered as a significant issue. It also specifies the distribution of cash flow during the course of the mine-life. Actually, LTPSP is a large-scale optimisation problem including large data-sets, multiple constraints, and uncertainty in the input factors that, has to be solved in a reasonable time. LTPSP, despite the valuable efforts of researchers, has not yet been well resolved. In this paper, hybrid models have been offered by the Lagrangian relaxation (LR) method with meta-heuristic methods, bat algorithm and particle swarm optimisation for solving the LTPSP due to the deterministic assumption and concerning the grade uncertainty. To bring update the Lagrange multipliers, the meta-heuristic algorithms have been applied. In terms of cumulative net present value, average ore grade, and computational time in a 12-year production period, the consequences achieved from the case studies point out that a solution close to optimisation can be presented by the LR-bat algorithm hybrid strategy in comparison with other methods. The results analysis has shown that the proposed method produces a near-optimal solution with a rational time that can be a good suggestion for utilising in the mining industry.

关键词： Open-pit mine long-term production scheduling grade uncertainty Lagrangian relaxation particle swarm optimisation algorithm bat algorithm

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Parallel asynchronous control strategy for target search with swarm robots

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INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION 2009年第3期1卷 151-163页

作者： Xue, Songdong Zhang, Jianhua Zeng, Jianchao Taiyuan Univ Sci & Technol Div Syst Simulat & Comp Applicat Taiyuan 030024 Peoples R China Lanzhou Univ Technol Coll Elect & Informat Engn Lanzhou 730050 Peoples R China

Upon mapping swarm robots search to particle swarm optimisation (PSO) and proposing concept of lime-varying character swarm (TVCS), the authors extend PSO to model swarm robotic system. Based on control principle of expected evolution position, an asynchronous communication policy is presented. Robot detects target signals in parallel to decide expected evolution position. The required time steps for completing the distance between two consecutive expected positions depend on kinematics constraints of robot. Meanwhile, robot evaluates positions it passes in every time step, updating its cognition as soon as when a better finding of itself has been found, updating shared information and broadcasting within TVCS if a better finding of swami appears. Either listening change of shared information or reaching the current expected position, robot starts to compute new expected position and turn out next control round. Simulation results indicate that the presented communication strategy has advantage over popular ones in search efficiency.

关键词： swarm robots target search particle swarm optimisation algorithm parallel asynchronous control communication strategy

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Relaxed stabilisation criterion for discrete T-S fuzzy systems by minimum-type piecewise non-quadratic Lyapunov function

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IET CONTROL THEORY AND APPLICATIONS 2012年第12期6卷 1918-1925页

作者： Chen, Y. -J. Ohtake, H. Tanaka, K. Wang, W. -J. Wang, H. O. Natl Cent Univ Dept Elect Engn Jhongli 32001 Taiwan Univ Electrocommun Dept Mech Engn & Intelligent Syst Chofu Tokyo 1828585 Japan Boston Univ Dept Aerosp & Mech Engn Boston MA 02215 USA

Piecewise Lyapunov functions and non-quadratic Lyapunov functions have been employed to analyse Takagi-Sugeno (T-S) fuzzy systems for getting relaxed results in the literature. Nevertheless, until now piecewise non-quadratic Lyapunov functions have not been used to design T-S fuzzy control systems. Motivated by the aforementioned concerns, this study utilises the minimum-type piecewise non-quadratic Lyapunov function to design the discrete T-S fuzzy control system. Based on the piecewise non-quadratic Lyapunov function, the switching non-parallel distributed compensation control law is proposed to obtain the relaxed stabilisation criterion. Owing to that some conditions of the proposed criterion are bilinear matrix inequalitiy conditions, the particle swarm optimisation algorithm is applied for finding out the solution of the criterion. An example is provided to illustrate the effectiveness of the proposed criterion.

关键词： optimisation techniques particle swarm optimisation discrete T-S fuzzy systems minimum-type piecewise nonquadratic Lyapunov function Takagi-Sugeno fuzzy systems discrete systems switching nonparallel distributed compensation control law stability control system synthesis Stability in control theory Control system analysis and synthesis methods Fuzzy control relaxed stabilisation criterion T-S fuzzy control system design compensation bilinear matrix inequalitiy conditions distributed control Lyapunov methods fuzzy control Discrete control systems piecewise linear techniques particle swarm optimisation algorithm

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Hybrid control of aggregated thermostatically controlled loads: step rule, parameter optimisation, parallel and cascade structures

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IET GENERATION TRANSMISSION & DISTRIBUTION 2016年第16期10卷 4149-4157页

作者： Ma, Kai Yuan, Chenliang Liu, Zhixin Yang, Jie Guan, Xinping Yanshan Univ Sch Elect Engn Qinhuangdao 066004 Peoples R China Shanghai Jiao Tong Univ Dept Automat Key Lab Syst Control & Informat Proc Minist Educ Shanghai 200240 Peoples R China

This study proposes hybrid control strategies for aggregated thermostatically controlled loads (TCLs) in order to provide ancillary service. The on/off control strategy and the setpoint-regulation strategy are two typical control strategies. In order to reduce the tracking errors of the two control strategies, two improved methods were developed. The first method dispatches the aggregated loads to the automatic generation control signal following a step rule based on the state of charge. The second method optimises the controller parameters of the setpoint-regulation strategy by the Powell optimisation algorithm. Based on these two improved methods, the hybrid control strategies with parallel and cascade control structures were established by dividing the TCLs into two clusters, and the optimal allocations of the loads, the reference signal and the tracking error between the two clusters were obtained by the particle swarm optimisation algorithm. The simulation results demonstrate that the hybrid control strategies can reduce the errors in load following.

关键词： particle swarm optimisation load regulation controllers aggregated thermostatically controlled loads parameter optimisation cascade structures parallel structures hybrid control strategies thermostatically controlled loads setpoint-regulation strategy control strategies tracking errors control strategies automatic generation control signal controller parameters Powell optimisation algorithm particle swarm optimisation algorithm

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Robust possibilistic programming for joint order batching and picker routing problem in warehouse management

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2021年第14期59卷 4434-4452页

作者： Attari, Mahdi Yousefi Nejad Torkayesh, Ali Ebadi Malmir, Behnam Jami, Ensiyeh Neyshabouri Islamic Azad Univ Dept Ind Engn Bonab Branch Bonab Iran Sabanci Univ Fac Engn & Nat Sci Istanbul Turkey Univ Virginia Dept Syst & Informat Engn Charlottesville VA USA Org Ind Mine & Trade Expert Ind East Azarbatjan Iran Virginia Tech Dept Business Informat Technol Pamplin Coll Business Blacksburg VA USA

Decisions made for designing and operating a warehouse system are of great significance. These operational decisions are strongly affected by total logistics costs, including investment and direct operating costs. The number of orders made by customers in the logistics section of warehouse management is very high because the number, type of products and items ordered by different customers vary broadly. However, machines layout for picking up products at logistics centres is minimal, inflexible, and, in some cases, inconclusive. In this study, we address joint order batching procedures of orders considering picker routing problem as a mixed-integer programming model. Extensive numerical experiments were generated in small, medium, and large sizes. In order to consider the uncertainty of parameters, we applied robust possibilistic programming for this problem. Three different meta-heuristic algorithms;genetic algorithm, particle swarm optimisation algorithm, and honey artificial bee colony algorithms are used as solution approaches to solve the formulated model. The performance of solution approaches over the problem was analysed using several test indexes. In all three group examples, there was no significant difference among mean values of the objective function, while there was a remarkable difference among computing times.

关键词： joint order batching picker routing genetic algorithm particle swarm optimisation algorithm artificial bee colony algorithms warehouse design warehousing systems

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Monte-Carlo based approach to consider the cost of voltage dip and long duration interruption in optimal planning of SDGs

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IET GENERATION TRANSMISSION & DISTRIBUTION 2018年第8期12卷 1856-1865页

作者： Eslami, Ahmadreza Golshan, Mohammad Esmail Hamedani Isfahan Univ Technol Dept Elect & Comp Engn Esfahan Iran

Voltage dip and long duration interruption (LDI) are among the most costly power quality phenomena. In this study, a Monte-Carlo based approach is proposed to consider the cost of sensitive loads disruption caused by dip and LDI in the optimal planning of synchronous distributed generations (SDGs). The idea is to link between trip probability due to dip and LDI and their yearly costs by employing Monte-Carlo simulation and acquiring their total costs during the planning horizon. The addition of disruption cost along with the traditional planning objectives like network upgrade cost and loss cost allows utilities to include the customer's perception during planning. A formula for the probability of disruption due to dip is derived and a modified Monte-Carlo approach is proposed. The methodology is illustrated on the distribution level of the IEEE 30-bus system and the optimisation problem is solved by particle swarm optimisation algorithm. The results demonstrate that the sensitive loads performance is improved from the dip standpoint in the presence of SDGs. However, the LDI cost is either not affected or aggravated by the presence of SDGs depending on the protection model. The total disruption cost is decreased.

关键词： distributed power generation Monte Carlo methods power supply quality power distribution planning particle swarm optimisation power distribution protection Monte-Carlo based approach voltage dip long duration interruption optimal planning SDG LDI power quality phenomena synchronous distributed generations trip probability network upgrade cost loss cost distribution level IEEE 30-bus system particle swarm optimisation algorithm sensitive loads performance dip standpoint protection model

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Multi-scale assimilation of root zone soil water predictions

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HYDROLOGICAL PROCESSES 2011年第20期25卷 3158-3172页

作者： Lu, Haishen Yu, Zhongbo Horton, Robert Zhu, Yonghua Wang, Zhenlong Hao, Zhenchun Xiang, Long Hohai Univ State Key Lab Hydrol Water Resources & Hydraul En Nanjing 210098 Peoples R China Univ Nevada Dept Geosci Las Vegas NV 89154 USA Iowa State Univ Dept Agron Ames IA 50011 USA Key Lab Water Resources Anhui Prov Bengbu 233000 Peoples R China

When hydrology model parameters are determined, a traditional data assimilation method (such as Kalman filter) and a hydrology model can estimate the root zone soil water with uncertain state variables (such as initial soil water content). The simulated result can be quite good. However, when a key soil hydraulic property, such as the saturated hydraulic conductivity, is overestimated or underestimated, the traditional soil water assimilation process will produce a persistent bias in its predictions. In this paper, we present and demonstrate a new multi-scale assimilation method by combining the direct insertion assimilation method, particle swarm optimisation (PSO) algorithm and Richards equation. We study the possibility of estimating root zone soil water with a multi-scale assimilation method by using observed in situ data from the Wudaogou experiment station, Huaihe River Basin, China. The results indicate there is a persistent bias between simulated and observed values when the direct insertion assimilation surface soil water content is used to estimate root zone soil water contents. Using a multi-scale assimilation method (PSO algorithm and direct insertion assimilation) and an assumed bottom boundary condition, the results show some obvious improvement, but the root mean square error is still relatively large. When the bottom boundary condition is similar to the actual situation, the multi-scale assimilation method can well represent the root zone soil water content. The results indicate that the method is useful in estimating root zone soil water when available soil water data are limited to the surface layer and the initial soil water content even when the soil hydraulic conductivities are uncertain. Copyright (C) 2011 John Wiley & Sons, Ltd.

关键词： surface soil water content root zone soil water content Richards equation multi-scale assimilation method particle swarm optimisation algorithm

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