The Experts below are selected from a list of 128364 Experts worldwide ranked by ideXlab platform
Fernandez Carlos - One of the best experts on this subject based on the ideXlab platform.
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A novel streamlined particle-unscented Kalman Filtering Method for the available energy prediction of lithium-ion batteries considering the time-varying temperature-current influence.
'Wiley', 2021Co-Authors: Zhang Liang, Wang Shunli, Zou Chuanyun, Fan Yongcun, Jin Siyu, Fernandez CarlosAbstract:Effective energy prediction is of great importance for the operational status monitoring of high-power lithium-ion battery packs. It should be embedded in the battery system performance evaluation, energy management, and safety protection. A new Streamlined Particle-Unscented Kalman Filtering Method is proposed to predict the available energy of lithium-ion batteries, in which an Adaptive-Dual Unscented Transform treatment is conducted to realize the precise mathematical expression of its working conditions. For the accurate mathematical description purpose, an improved Synthetic-Electrical Equivalent Circuit modeling Method is introduced into the internal effect equivalent process considering the influence of time-varying temperature and current conditions. As can be known from the experimental results, the proposed prediction Method has a maximum estimation error of 2.27% and an average error of 0.80%, for the complex varying-current Beijing Bus Dynamic Stress Test. Under the Urban Dynamometer Driving Schedule working conditions, the available energy prediction has high accuracy with a maximum error of 1.83% and a voltage traction error of 3.28%. It provides vehicle-mounted available energy prediction schemes for effective management and safety protection of high-power lithium-ion batteries. Highlights: A new Streamlined Particle-Unscented Kalman Filtering Method is proposed to predict the available energy of lithium-ion batteries. Improved Synthetic-Electrical Equivalent Circuit modeling strategies are established to describe the nonlinear battery characteristics. Adopted predictive correction is investigated by considering the time-varying temperature and current influence. For effective convergence, an adaptive windowing function factor is introduced into the correction process with a maximum estimation error of 2.27% and an average error of 0.80% for the complex varying-current Beijing Bus Dynamic Stress Test working conditions. The vehicle battery available energy prediction is realized with a maximum error of 1.83% and a maximum voltage traction error of 3.28% for the Urban Dynamometer Driving Schedule working conditions
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A novel bias compensation recursive least square‐multiple weighted dual extended Kalman Filtering Method for accurate state‐of‐charge and state‐of‐health co‐estimation of lithium‐ion batteries.
'Wiley', 2021Co-Authors: Qiao Jialu, Wang Shunli, Yu Chunmei, Shi Weihao, Fernandez CarlosAbstract:Abstract - State-of-charge and state-of-health of power lithium-ion batteries are two important state parameters for battery management system monitoring. To accurately estimate the state-of-charge and state-of-health of in real time, the ternary lithium-ion battery is taken as the research object, and a novel bias compensation recursive least square-multiple weighted dual extended Kalman Filtering Method is proposed innovatively. The noise variance estimation is introduced to compensate the parameters identified by the general least square Method to realize the accurate identification. The estimation value is corrected by using the residual and Kalman gain at multiple times, and different weights are configured for each residual according to the amount of information contained. The data of different complex conditions are used to verify the feasibility of the proposed algorithm, the results show that the root-mean-square error of bias compensation recursive least square-multiple weighted dual extended Kalman Filtering under dynamic stress test and Beijing bus dynamic stress test condition can be controlled within 1.62% and 2.70% in state-of charge estimation, 0.17% and 0.81% in state-of-health estimation, which verifies that the proposed algorithm in this research has good running effect. The novel bias compensation recursive least square-multiple weighted dual extended Kalman Filtering Method lays a theoretical foundation for the safe operation of electric vehicles
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A novel streamlined particle-unscented Kalman Filtering Method for the available energy prediction of lithium-ion batteries considering the time-varying temperature-current influence.
'Wiley', 2021Co-Authors: Zhang Liang, Wang Shunli, Zou Chuanyun, Fan Yongcun, Jin Siyu, Fernandez CarlosAbstract:Effective energy prediction is of great importance for the operational status monitoring of high-power lithium-ion battery packs. It should be embedded in the battery system performance evaluation, energy management, and safety protection. A new Streamlined Particle-Unscented Kalman Filtering Method is proposed to predict the available energy of lithium-ion batteries, in which an Adaptive-Dual Unscented Transform treatment is conducted to realize the precise mathematical expression of its working conditions. For the accurate mathematical description purpose, an improved Synthetic-Electrical Equivalent Circuit modeling Method is introduced into the internal effect equivalent process considering the influence of time-varying temperature and current conditions. As can be known from the experimental results, the proposed prediction Method has a maximum estimation error of 2.27% and an average error of 0.80%, for the complex varying-current Beijing Bus Dynamic Stress Test. Under the Urban Dynamometer Driving Schedule working conditions, the available energy prediction has high accuracy with a maximum error of 1.83% and a voltage traction error of 3.28%. It provides vehicle-mounted available energy prediction schemes for effective management and safety protection of high-power lithium-ion batteries
Yuanman Zheng - One of the best experts on this subject based on the ideXlab platform.
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preferential Filtering for gravity anomaly separation
Computers & Geosciences, 2013Co-Authors: Lianghui Guo, Xiaohong Meng, Zhaoxi Chen, Yuanman ZhengAbstract:We present the preferential Filtering Method for gravity anomaly separation based on Green equivalent-layer concept and Wiener filter. Compared to the conventional upward continuation and the preferential continuation, the preferential Filtering Method has the advantage of no requirement of continuation height. The Method was tested both on the synthetic gravity data of a model of multiple rectangular prisms and on the real gravity data from a magnetite area in Jilin Province, China. The results show that the preferential Filtering Method produced better separation of gravity anomaly than both the conventional low-pass Filtering and the upward continuation.
Jonas Mureika - One of the best experts on this subject based on the ideXlab platform.
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fractal dimensions in perceptual color space a comparison study using jackson pollock s art
Chaos, 2005Co-Authors: Jonas MureikaAbstract:The fractal dimensions of color-specific paint patterns in various Jackson Pollock paintings are calculated using a Filtering process that models perceptual response to color differences (L*a*b* color space). The advantage of the L*a*b* space Filtering Method over traditional red-green-blue (RGB) spaces is that the former is a perceptually uniform (metric) space, leading to a more consistent definition of “perceptually different” colors. It is determined that the RGB Filtering Method underestimates the perceived fractal dimension of lighter-colored patterns but not of darker ones, if the same selection criteria is applied to each. Implications of the findings to Fechner’s “principle of the aesthetic middle” and Berlyne’s work on perception of complexity are discussed.
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fractal dimensions in perceptual color space a comparison study using jackson pollock s art
arXiv: Physics and Society, 2005Co-Authors: Jonas MureikaAbstract:The fractal dimensions of color-specific paint patterns in various Jackson Pollock paintings are calculated using a Filtering process which models perceptual response to color differences ($\Lab$ color space). The advantage of the $\Lab$ space Filtering Method over traditional RGB spaces is that the former is a perceptually-uniform (metric) space, leading to a more consistent definition of ``perceptually different'' colors. It is determined that the RGB Filtering Method underestimates the perceived fractal dimension of lighter colored patterns but not of darker ones, if the same selection criteria is applied to each. Implications of the findings to Fechner's 'Principle of the Aesthetic Middle' and Berlyne's work on perception of complexity are discussed.
Jiazhu Xu - One of the best experts on this subject based on the ideXlab platform.
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An Industrial DC Power Supply System Based on an Inductive Filtering Method
IEEE Transactions on Industrial Electronics, 2012Co-Authors: Yong Li, Sven Rüberg, Longfu Luo, Dechang Yang, Christian Rehtanz, Jiazhu XuAbstract:This paper proposes a new direct current (dc) power supply system based on an inductive Filtering Method for one industrial dc load. The operating mechanism of the new inductive Filtering Method is analyzed, and then, the harmonic model and the equivalent model are established. Moreover, the impedance conditions for the implementation of the inductive Filtering Method are presented, and the influence of the Filtering loop's impedance on the Filtering performance is clarified. Both the simulation and the experimental study on one practical inductive-Filtering-based industrial dc supply system for chemical electrolysis are used to validate the theoretical analysis. The research results show that the inductive Filtering Method not only greatly reduces the harmonic magnetic flux in the rectifier transformer but also prevents harmonic currents from flowing into the primary (grid) winding of the rectifier transformer. It presents good Filtering and reactive power compensating performances to public networks and also increases the operating efficiency of the industrial dc power supply system itself.
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A New Converter Transformer and a Corresponding Inductive Filtering Method for HVDC Transmission System
IEEE Transactions on Power Delivery, 2008Co-Authors: Yong Li, Jiazhu Xu, Ji Li, Bo HuAbstract:A new converter transformer and an inductive Filtering Method are presented to solve the existing problems of the traditional converter transformer and the passive Filtering Method of the high-voltage direct current (HVDC) system. It adopts the ampere-turn balance of the transformer as the Filtering mechanism. A tap at the linking point of the prolonged winding and the common winding of the secondary windings is connected with the LC resonance circuit. It can realize the goal that once theharmonic current flowsinto the prolonged winding, the common winding will induct the opposite harmonic current to balance it by the zero impedance design of the common winding and the proper configuration of LC parameters, so there will be no inductive harmonic current in the primary winding. Moreover, the reactive power that the converter needs can be partly compensated in the secondary winding. Simulation results have verified the correctness of the theoretical analysis. The new converter transformer can greatly reduce the harmonic content in the primary winding, loss, and noise generated by harmonics in the transformer, and the difficulty of the transformer's insulation design.
Wei Wu - One of the best experts on this subject based on the ideXlab platform.
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extraction of mismatch negativity using a resampling based spatial Filtering Method
Journal of Neural Engineering, 2013Co-Authors: Wei Wu, Chaohua WuAbstract:Objective. It is currently a challenge to extract the mismatch negativity (MMN) waveform on the basis of a small number of EEG trials, which are typically unbalanced between conditions. Approach. In order to address this issue, a Method combining the techniques of resampling and spatial Filtering is proposed in this paper. Specifically, the first step of the Method, termed ‘resampling difference’, randomly samples the standard and deviant sweeps, and then subtracts standard sweeps from deviant sweeps. The second step of the Method employs the spatial filters designed by a signal-to-noise ratio maximizer (SIM) to extract the MMN component. The SIM algorithm can maximize the signal-to-noise ratio for event-related potentials (ERPs) to improve extraction. Simulation data were used to evaluate the influence of three parameters (i.e. trial number, repeated-SIM times and sampling times) on the performance of the proposed Method. Main results. Results demonstrated that it was feasible and reliable to extract the MMN waveform using the Method. Finally, an oddball paradigm with auditory stimuli of different frequencies was employed to record a few trials (50 trials of deviant sweeps and 250 trials of standard sweeps) of EEG data from 11 adult subjects. Results showed that the Method could effectively extract the MMN using the EEG data of each individual subject. Significance. The extracted MMN waveform has a significantly larger peak amplitude and shorter latencies in response to the more deviant stimuli than in response to the less deviant stimuli, which agreed with the MMN properties reported in previous literature using grand-averaged EEG data of multi-subjects.