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| 1 | Semi-supervised estimation of capacity degradation for lithium ion batteries with electrochemical impedance spectroscopy显示文摘Machine learning-based methods have emerged as a promising solution to accurate battery capacity estimation for battery management systems.However,they are generally developed in a supervised manner which requires a considerable number of input features and corresponding capacities,leading to prohibitive costs and efforts for data collection.In response to this issue,this study proposes a convolutional neural network(CNN)based method to perform end-to-end capacity estimation by taking only raw impedance spectra as input.More importantly,an input reconstruction module is devised to effectively exploit impedance spectra without corresponding capacities in the training process,thereby significantly alleviating the cost of collecting training data.Two large battery degradation datasets encompassing over 4700 impedance spectra are developed to validate the proposed method.The results show that accurate capacity estimation can be achieved when substantial training samples with measured capacities are given.However,the estimation performance of supervised machine learning algorithms sharply deteriorates when fewer samples with measured capacities are available.In this case,the proposed method outperforms supervised benchmarks and can reduce the root mean square error by up to 50.66%.A further validation under different current rates and states of charge confirms the effectiveness of the proposed method.Our method provides a flexible approach to take advantage of unlabelled samples for developing data-driven models and is promising to be generalised to other battery management tasks. | Rui Xiong Jinpeng Tian Weixiang Shen Jiahuan Lu Fengchun Sun | 2023 | Journal of Energy Chemistry2023，，1： | 1 |
| 2 | A novel intelligent control system for flue-curing barns based on real-time image features显示文摘 | Juan Wu Simon X. Yang Fengchun Tian | 2014 | Biosystems Engineering2014，，： | 1 |
| 3 | Speckle reduction by adaptive window anisotropic dif-fusion显示文摘 | LIU Guojin ZENG Xiaoping TIAN Fengchun | 2009 | Signal Processing2009，89，： | 1 |
| 4 | Speckle reduction by adaptive window anisotropic diffusion显示文摘 | Liu Guojin Zeng Xiaoping Tian Fengchun | 2009 | Signal Processing2009，89，11： | 1 |
| 5 | A Modified Statistically Optimal Null Filter Method for Recognizing Protein-coding Regions显示文摘Computer-aided protein-coding gene prediction in uncharacterized genomic DNA sequences is one of the most important issues of biological signal processing.A modified filter method based on a statistically optimal null filter(SONF) theory is proposed for recognizing protein-coding regions.The square deviation gain(SDG) between the input and output of the model is used to identify the coding regions.The effective SDG amplification model with Class I and Class II enhancement is designed to suppress the non-coding regions.Also,an evaluation algorithm has been used to compare the modified model with most gene prediction methods currently available in terms of sensitivity,specificity and precision.The performance for identification of protein-coding regions has been evaluated at the nucleotide level using benchmark datasets and 91.4%,96%,93.7% were obtained for sensitivity,specificity and precision,respectively.These results suggest that the proposed model is potentially useful in gene finding field,which can help recognize protein-coding regions with higher precision and speed than present algorithms. | Lei Zhang Fengchun Tian Shiyuan Wang | 2012 | Genomics, Proteomics & Bioinformatics2012，10，3： | 1 |
| 6 | Applications of representation method for DNA sequences based on symbolic dynamics显示文摘 | Wang Shiyuan Tian Fengchun Feng Wenjiang | | 0，，： | 1 |
| 7 | A novel representation approach to DNA sequence and its application显示文摘 | Wang Shiyuan Tian Fengchun Liu Xiao | | 0，，04： | 1 |
| 8 | A novel classifier ensemble for recognition of multiple indoor air contaminants by an electronic nose显示文摘 | Dang Lijun Tian Fengchun Zhang Lei | 2014 | Sensors and Actuators A:Physical2014，207，： | 1 |
| 9 | Fractional order battery modelling methodologies for electric vehicle applications:Recent advances and perspectives显示文摘Accurate modelling of lithium ion batteries is crucial for battery management in electric vehicles.Recent studies have revealed the fractional order nature of lithium ion batteries,leading to fractional order modelling techniques.In this paper,a comprehensive review of the fractional order battery models and their applications in battery management of electric vehicles is provided from the perspectives of frequency and time domains.In the frequency domain,the fractional order models to fit electrochemical impedance spectroscopy data are investigated,followed by their applications in health diagnosis,battery heating and charging strategies.In the time domain,the fractional order models adopted for voltage simulation are discussed,followed by their applications in battery state estimation and fault diagnosis.Finally,from the perspectives of time domain and frequency domain applications,critical challenges and research trends for future work in terms of fractional order modelling are highlighted to advance the development of next-generation battery management. | TIAN JinPeng XIONG Rui SHEN WeiXiang SUN FengChun | 2020 | Science China(Technological Sciences)2020，63，11： | 0 |
| 10 | Development of a pure electric road sweeper显示文摘 | 梁新成 Zhang Jun Sun Fengchun Tian Le | 2010 | High Technology Letters2010，16，1： | 0 |
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