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学者姓名：张红光
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Abstract ：
Accurately estimating the state of charge (SOC) and state of power (SOP) of the battery is essential for optimizing the use of electric quantity and ensuring the safe and efficient operation and energy management of the battery system of electric vehicles. In this paper, a particle swarm optimization algorithm is used to identify the model parameters of lithium-ion batteries under wide temperature range, and a SOC estimation method of adaptive cubature Kalman filter algorithm based on singular value decomposition (SVD-ACKF) is proposed. The Cholesky decomposition of covariance of state variables is replaced by singular value decomposition, which successfully avoids the problem of the non-positive definite matrix during the adaptive updating of the cubature Kalman filter algorithm, and improves the convergence stability of the iterative computation process. Based on accurate SOC estimation at each temperature, the key constraints in this study are composed of the combination of the SOC, voltage, and current of the battery, and changes in battery model parameters due to ambient temperature are considered, developing an SOP estimation strategy under multi-constraint conditions, realizing the joint estimation of SOC and SOP, verifying the feasibility of the proposed state estimation algorithm in different ambient temperatures. The results show that the maximum error of SOC estimation under different ambient temperatures is less than 0.015, and the SOC estimation error of the proposed method is the smallest compared with the extended Kalman filter (EKF) and the cubature Kalman filter (CKF), and the average relative errors of peak charge power and peak discharge power estimation with a duration of 30 s at 25 degrees C can be kept within 2.5% and 1.5%, respectively. It is proved that the proposed method has good accuracy and adaptability.
Keyword ：
State of charge State of charge State of power State of power Lithium-ion batteries Lithium-ion batteries SVD-ACKF algorithm SVD-ACKF algorithm
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| GB/T 7714 | Wang, Shuo , Xu, Yonghong , Zhang, Hongguang et al. An adaptive cubature Kalman filter algorithm based on singular value decomposition for joint estimation of state of charge and state of power for lithium-ion batteries under wide temperature range [J]. | IONICS , 2024 . |
| MLA | Wang, Shuo et al. "An adaptive cubature Kalman filter algorithm based on singular value decomposition for joint estimation of state of charge and state of power for lithium-ion batteries under wide temperature range" . | IONICS (2024) . |
| APA | Wang, Shuo , Xu, Yonghong , Zhang, Hongguang , Kuang, Rao , Zhang, Jian , Liu, Baicheng et al. An adaptive cubature Kalman filter algorithm based on singular value decomposition for joint estimation of state of charge and state of power for lithium-ion batteries under wide temperature range . | IONICS , 2024 . |
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Abstract ：
Lithium-ion battery disposal is becoming an increasingly important issue with the rapid growth of Electric Vehicles (EVs) regarding resource conservation and environmental sustainability. It is considered the most suitable solution to reuse rather than dispose of retired batteries. However, the precision in estimating the battery states is of great importance to ensure the operational safety and efficiency of reused battery packs. This study proposes a joint estimation method to predict the State of Charge (SOC) and the peak power capability for reused battery packs considering inconsistency. The primary content of this work is described as follows. (1) This paper designs an improved screening method for evaluating the consistency of the reused batteries that are used to connect to the series battery pack. (2) A second-order RC model is selected as the cell mean model (CMM) to represent the overall performance of the reused battery pack. On this basis, the mean SOC is estimated by using Sage-Husa adaptive algorithm and extended Kalman filter (SH-AEKF), whereas the peak power capability is evaluated by considering multiple limitations. (3) An experiment is conducted to evaluate the robustness of the joint estimation method. The results show that the maximum absolute error of SOC estimation is below +/- 3 % while the mean absolute percentage error (MAPE) of peak power capability estimation could be limited to less than 3.5 %. This study indicates the high accuracy and reliability of the proposed joint estimation method for retired battery packs.
Keyword ：
Battery pack Battery pack Screening method Screening method Peak power capability Peak power capability Reused battery Reused battery State of charge State of charge
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| GB/T 7714 | Zhang, Yujie , Liu, Baicheng , Zhang, Hongguang et al. Joint estimation of SOC and peak power capability for series reused battery pack based on screening process method [J]. | ENERGY , 2024 , 313 . |
| MLA | Zhang, Yujie et al. "Joint estimation of SOC and peak power capability for series reused battery pack based on screening process method" . | ENERGY 313 (2024) . |
| APA | Zhang, Yujie , Liu, Baicheng , Zhang, Hongguang , Kuang, Rao , Xu, Yonghong , Zhang, Jian et al. Joint estimation of SOC and peak power capability for series reused battery pack based on screening process method . | ENERGY , 2024 , 313 . |
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Abstract ：
Compressed air energy storage will have good development prospects because of its exceptional safety and reliability, low economic cost, zero carbon emissions, and pollution-free environmentally friendly characteristics, which meet the needs of sustainable and green development. In view of the problems of large volume, great number of equipment, and poor flexibility of traditional compressed air energy storage equipment, this article built a compressed air experimental bench based on pneumatic motor and conducted integrated pneumatic motor compression/expansion experiments. The effects of key parameters such as speed, torque and current on the performance of pneumatic motor under different modes are investigated, providing reference for the application and promotion of small compressed air energy storage systems. The results indicate that in the expansion mode of the pneumatic motor, the total efficiency and power output of the motor can reach up to 14.01 % and 1257.87 W. Its high power output and economic operation are concentrated within the medium range of rotation speed and current, respectively, with a certain cooling effect achieved in this mode. In compression mode, the maximum output power of the motor can reach 3696.33 W, while the energy efficiency is up to 78.39 %. The operating parameters such as torque and current are basically positively correlated with the system performance parameters. The integrated system is flexible, saves space, and has certain feasibility.
Keyword ：
Parameter performance Parameter performance Integrated compression and expansion Integrated compression and expansion Compressed air energy storage Compressed air energy storage Pneumatic motor Pneumatic motor
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| GB/T 7714 | Zheng, Hao , Xu, Yonghong , Zhang, Hongguang et al. Performance study of integrated compressor/expander based on small-scale compressed air energy storage system [J]. | JOURNAL OF ENERGY STORAGE , 2024 , 105 . |
| MLA | Zheng, Hao et al. "Performance study of integrated compressor/expander based on small-scale compressed air energy storage system" . | JOURNAL OF ENERGY STORAGE 105 (2024) . |
| APA | Zheng, Hao , Xu, Yonghong , Zhang, Hongguang , Zhang, Jian , Yang, Fubin , Yang, Hailong et al. Performance study of integrated compressor/expander based on small-scale compressed air energy storage system . | JOURNAL OF ENERGY STORAGE , 2024 , 105 . |
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Abstract ：
This paper proposed a single-piston free piston expander-linear generator (SFPE-LG) prototype applied to organic Rankine cycle systems. Two valve timing control strategies, namely, time control strategy (TCS) and position control strategy (PCS), were developed. Based on the experimental data, a back propagation neural network (BPNN) prediction model was established. The effects of structural parameters such as neural network layers, transfer function, training function, hidden layer nodes, and learning rate on the prediction accuracy of this BPNN model were discussed. The training and prediction accuracy of the BPNN model was verified using 5-fold cross-validation and Wilcoxon signed-rank test. Moreover, the BPNN model was integrated with a genetic algorithm to predict and optimize the maximum output power of the SFPE-LG. The results showed that the BPNN model used to predict the motion characteristics and output performance of the SFPE-LG exhibits strong learning ability and high prediction accuracy. Notably, the prediction accuracy of the BPNN model is significantly higher under the PCS compared to TCS. The effect of hidden layer nodes on mean square error (MSE) and correlation coefficient (R) is greater than that of the learning rate. When the number of hidden layer nodes exceeds 30, the BPNN model consistently achieves low MSE and high R. The optimization results showed that the SFPE-LG can obtain a maximum output power of 141.69 W under the TCS, when the working parameters are inlet pressure of 0.7 MPa, intake duration of 35 ms, load resistance of 67 omega, and expansion duration of 104 ms, respectively.
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| GB/T 7714 | Li, Jian , Zuo, Zhengxing , Jia, Boru et al. Performance Prediction and Optimization of Single-Piston Free Piston Expander-Linear Generator Based on Machine Learning and Genetic Algorithm [J]. | INTERNATIONAL JOURNAL OF ENERGY RESEARCH , 2024 , 2024 . |
| MLA | Li, Jian et al. "Performance Prediction and Optimization of Single-Piston Free Piston Expander-Linear Generator Based on Machine Learning and Genetic Algorithm" . | INTERNATIONAL JOURNAL OF ENERGY RESEARCH 2024 (2024) . |
| APA | Li, Jian , Zuo, Zhengxing , Jia, Boru , Feng, Huihua , Zhang, Hongguang , Mei, Bingang . Performance Prediction and Optimization of Single-Piston Free Piston Expander-Linear Generator Based on Machine Learning and Genetic Algorithm . | INTERNATIONAL JOURNAL OF ENERGY RESEARCH , 2024 , 2024 . |
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Abstract ：
Solid oxide fuel cells (SOFCs) are an effective and sustainable energy conversion technology. As operating temperatures decrease, metal interconnects and supports are widely employed in SOFCs. It is critical to apply a protective coat on ferritic stainless steel (FSS) to suppress Cr evaporation and element interdiffusion under high temperatures. Electrophoretic deposition (EPD) is a promising approach for depositing metal oxides on FSS substrate. Here, a method based on 3D multi-physical simulation and orthogonal experimental design was proposed to optimize deposition parameters, including applied voltage, deposition time, and electrode distance. The EPD process to deposit Mn1.5Co1.5O4 particles in a suspension of ethanol and isopropanol was simulated and the effects of these three factors on the film thickness and uniformity were analyzed. The results indicate that applied voltage has the greatest impact on deposition thickness, followed by deposition time and electrode distance. Meanwhile, deposition time exhibits a more significant effect on film unevenness than applied voltage. Additionally, the particle-fluid coupling phenomenon was analyzed during the EPD process. In practice, these deposition parameters must be selected appropriately and the deposition time must be controlled to obtain a uniform coating. The proposed method can reduce cost and shorten the design period.
Keyword ：
electrophoretic deposition electrophoretic deposition orthogonal experiment orthogonal experiment solid oxide fuel cell solid oxide fuel cell multi-physical simulation multi-physical simulation Mn1.5Co1.5O4 powder Mn1.5Co1.5O4 powder
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| GB/T 7714 | Zhou, Yaqin , Mao, Jingwen , Wang, Enhua et al. Parameters Optimization for Electrophoretic Deposition of Mn1.5Co1.5O4 on Ferritic Stainless Steel Based on Multi-Physical Simulation [J]. | JOURNAL OF THE ELECTROCHEMICAL SOCIETY , 2024 , 171 (6) . |
| MLA | Zhou, Yaqin et al. "Parameters Optimization for Electrophoretic Deposition of Mn1.5Co1.5O4 on Ferritic Stainless Steel Based on Multi-Physical Simulation" . | JOURNAL OF THE ELECTROCHEMICAL SOCIETY 171 . 6 (2024) . |
| APA | Zhou, Yaqin , Mao, Jingwen , Wang, Enhua , Zhang, Hongguang . Parameters Optimization for Electrophoretic Deposition of Mn1.5Co1.5O4 on Ferritic Stainless Steel Based on Multi-Physical Simulation . | JOURNAL OF THE ELECTROCHEMICAL SOCIETY , 2024 , 171 (6) . |
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Abstract ：
The organic Rankine cycle (ORC) system is an important technology for recovering energy from the waste heat of internal combustion engines, which is of significant importance for the improvement of fuel utilization. This study analyses the performance of vehicle ORC systems and proposes a rapid optimization method for enhancing vehicle ORC performance. This study constructed a numerical simulation model of an internal combustion engine-ORC waste heat recovery system based on GT-Suite software v2016. The impact of key operating parameters on the performance of two organic Rankine cycles: the simple organic Rankine cycle (SORC) and the recuperative organic Rankine cycle (RORC) was investigated. In order to facilitate real-time prediction and optimization of system performance, a data-driven rapid prediction model of the performance of the waste heat recovery system was constructed based on an artificial neural network. Meanwhile, the NSGA-II multi-objective algorithm was used to investigate the competitive relationship between different performance objective functions. Furthermore, the optimal operating parameters of the system were determined by utilizing the TOPSIS method. The results demonstrate that the highest thermal efficiencies of the SORC and RORC are 6.21% and 8.61%, respectively, the highest power outputs per unit heat transfer area (POPAs) are 6.98 kW/m2 and 8.99 kW/m2, respectively, the lowest unit electricity production costs (EPC) are 7.22 x 10-2 USD/kWh and 3.15 x 10-2 USD/kWh, respectively, and the lowest CO2 emissions are 2.85 ton CO2,eq and 3.11 ton CO2,eq, respectively. The optimization results show that the RORC exhibits superior thermodynamic and economic performance in comparison to the SORC, yet inferior environmental performance.
Keyword ：
genetic algorithm genetic algorithm organic Rankine cycle organic Rankine cycle neural network neural network performance analysis and optimization performance analysis and optimization vehicle engine vehicle engine
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| GB/T 7714 | Wang, Xin , Chen, Xia , Xing, Chengda et al. Performance Analysis and Rapid Optimization of Vehicle ORC Systems Based on Numerical Simulation and Machine Learning [J]. | ENERGIES , 2024 , 17 (18) . |
| MLA | Wang, Xin et al. "Performance Analysis and Rapid Optimization of Vehicle ORC Systems Based on Numerical Simulation and Machine Learning" . | ENERGIES 17 . 18 (2024) . |
| APA | Wang, Xin , Chen, Xia , Xing, Chengda , Ping, Xu , Zhang, Hongguang , Yang, Fubin . Performance Analysis and Rapid Optimization of Vehicle ORC Systems Based on Numerical Simulation and Machine Learning . | ENERGIES , 2024 , 17 (18) . |
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Abstract ：
压缩空气储能具有寿命长、成本低、环境污染小等优点而备受关注，然而压缩空气储能系统存在能量密度和效率低的问题，本工作提出了气动马达并联工作模式以提高压缩空气储能系统的输出功率、能量转换效率和经济性。通过对比分析了在气动马达并联工作和单独工作时，关键参数变化对气动马达输出功率、经济性和能量转换效率的影响规律。为了将微型压缩空气储能系统的膨胀机和压缩机一体化，本工作研究了气动马达正转和反转的性能。气动马达既作为膨胀机又作为压缩机，可以双模式运行，提高设备的利用率，降低压缩空气储能系统的成本。与可再生能源发电相结合的应用场景中，变工况运行是压缩空气储能系统面临的一个关键问题。以储气罐压力变化和负荷需求波动为代表的多种变工况条件在系统运行过程中常常同时存在，本工作在变工况条件下，通过试验研究了关键因素对压缩空气储能系统性能的影响情况。试验结果表明，采用气动马达并联工作模式可以提高压缩空气储能系统的输出功率、能量转换效率和经济性。当进气压力为10.5 bar(1 bar=100 kPa)时，气动马达和发电机输出功率的最大值约为660 W和380 W。
Keyword ：
输出功率 输出功率 并联模式 并联模式 压缩空气储能系统 压缩空气储能系统 气动马达 气动马达
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| GB/T 7714 | 许永红 , 吴玉庭 , 张红光 et al. 基于气动马达的微型压缩空气储能系统的试验研究 [J]. | 储能科学与技术 , 2023 , 12 (06) : 1854-1861 . |
| MLA | 许永红 et al. "基于气动马达的微型压缩空气储能系统的试验研究" . | 储能科学与技术 12 . 06 (2023) : 1854-1861 . |
| APA | 许永红 , 吴玉庭 , 张红光 , 杨富斌 , 王焱 . 基于气动马达的微型压缩空气储能系统的试验研究 . | 储能科学与技术 , 2023 , 12 (06) , 1854-1861 . |
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Abstract ：
为了做好大学的"三全育人"工作,针对汽车文化这门公共选修课程,在建设课程思政方面进行思考与实践,如科学设计教学内容、精心挖掘课程思政元素、充分将课程思政元素与教学内容有机融合、高度重视现代教育技术手段和合理运用线下线上融合式教学等.通过任课教师和选课学生的共同努力,"三全育人"工作和课程思政建设均取得明显成效,汽车文化的教学工作获得选课学生的认可.
Keyword ：
课程思政 课程思政 三全育人 三全育人 公共选修课 公共选修课 线下线上融合式教学 线下线上融合式教学 汽车文化 汽车文化
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| GB/T 7714 | 张红光 , 王焱 , 闫栋 et al. 汽车文化公共选修课课程思政建设的思考与实践 [J]. | 高教学刊 , 2023 , 9 (10) : 27-30,35 . |
| MLA | 张红光 et al. "汽车文化公共选修课课程思政建设的思考与实践" . | 高教学刊 9 . 10 (2023) : 27-30,35 . |
| APA | 张红光 , 王焱 , 闫栋 , 许永红 , 杨一帆 , 李怡霞 et al. 汽车文化公共选修课课程思政建设的思考与实践 . | 高教学刊 , 2023 , 9 (10) , 27-30,35 . |
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Abstract ：
为了落实“三全育人”工作，针对“汽车文化”公共选修课程，在“课程思政”育人方面进行了探索与实践，如做好“课程思政”的总体设计方案和实施方案、精心挖掘“课程思政”元素和中国元素、推出高质量的“课程思政”教学案例、讲好汽车文化中的中国故事、合理运用“线下线上融合式教学”模式等。通过师生双方的共同努力，“课程思政”建设成效明显，课程教学工作得到了学校关注和学生认可。
Keyword ：
课程思政 课程思政 中国故事 中国故事 线下线上融合式教学 线下线上融合式教学 教学案例 教学案例 公共选修课 公共选修课 汽车文化 汽车文化
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| GB/T 7714 | 张红光 , 陈巍 , 王焱 et al. 课程思政与汽车文化中的中国故事 [J]. | 时代汽车 , 2023 , PageCount-页数: 4 (10) : 55-57,106 . |
| MLA | 张红光 et al. "课程思政与汽车文化中的中国故事" . | 时代汽车 PageCount-页数: 4 . 10 (2023) : 55-57,106 . |
| APA | 张红光 , 陈巍 , 王焱 , 许永红 , 杨富斌 , 张颖 . 课程思政与汽车文化中的中国故事 . | 时代汽车 , 2023 , PageCount-页数: 4 (10) , 55-57,106 . |
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Abstract ：
有机朗肯循环(ORC)是实现中低温热能高效利用的主要技术之一.选择适宜的工质和循环结构可以显著提高ORC的热力学性能.本文基于工质参数化模型提出一种ORC构型和工质的热力学评价方法.首先,通过建立的工质参数化模型实现了ORC工质物性参数和循环参数的协同优化,从而获得不同构型ORC在不同热源条件下的最高热效率,进而确定了ORC的最佳构型和最适热源温度.然后,分析了在最佳构型下优化得到的工质物性参数与实际工质之间的差异.最终,在优化得到的工质物性参数的基础上,通过建立多元线性回归模型实现了不同工质ORC热力学性能的准确预测.结果表明,回热式结构是ORC的最佳循环结构,其最佳热源温度为300℃;利用基于优化得到的工质物性参数建立的多元线性回归模型预测不同工质热力学性能时,相对误差范围为0.8％ ～-1％.
Keyword ：
有机朗肯循环(ORC) 有机朗肯循环(ORC) 最适热源温度 最适热源温度 循环结构 循环结构 参数化模型 参数化模型 工质评价 工质评价
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| GB/T 7714 | 闫栋 , 杨富斌 , 张红光 et al. 基于工质参数化建模的ORC不同构型热力学性能评价 [J]. | 大电机技术 , 2023 , (2) : 65-72 . |
| MLA | 闫栋 et al. "基于工质参数化建模的ORC不同构型热力学性能评价" . | 大电机技术 2 (2023) : 65-72 . |
| APA | 闫栋 , 杨富斌 , 张红光 , 许永红 , 李安生 . 基于工质参数化建模的ORC不同构型热力学性能评价 . | 大电机技术 , 2023 , (2) , 65-72 . |
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