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A pre-warning system of abnormal energy consumption in lead smelting based on LSSVR-RP-CI

Journal of Central South University 2019年第8期26卷 2175-2184页

作者： WANG Hong-cai FANG Hong-ru MENG Lei XU Feng-xiang School of Energy Science and Engineering Central South University Changsha 410083 China School of Automation Wuhan University of Technology Wuhan 430070 China Hubei Key Laboratory of Advanced Technology of Automotive Components Wuhan University of Technology Wuhan 430070 China

The pre-warning of abnormal energy consumption is important for energy conservation of industrial engineering. However, related studies on the lead smelting industries which usually have a huge energy consumption are rarely reported. Therefore, a pre-warning system was established in this study based on the intelligent prediction of energy consumption and the identification of abnormal energy consumption. A least square support vector regression (LSSVR) model optimized by the adaptive genetic algorithm was developed to predict the energy consumption in the process of lead smelting. A recurrence plots (RP) analysis and a confidence intervals (CI) analysis were conducted to quantitatively confirm the stationary degree of energy consumption and the normal range of energy consumption, respectively, to realize the identification of abnormal energy consumption. It is found the prediction accuracy of LSSVR model can exceed 90% based on the comparison between the actual and predicted data. The energy consumption is considered to be non-stationary if the correlation coefficient between the time series of periodicity and energy consumption is larger than that between the time series of periodicity and Lorenz. Additionally, the lower limit and upper limit of normal energy consumption are obtained.

关键词： lead smelting energy consumption least square support vector regression (LSSVR) recurrence plots (RP) confidence intervals (CI)

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A novel method of long-term aging prediction for proton exchange membrane fuel cell under the dynamic load cycling condition

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International Journal of Hydrogen Energy 2024年

作者： Yu, Xiaoran Yang, Yang Liu, Yanjun Zhu, Wenchao Xie, Changjun School of Automation Wuhan University of Technology Wuhan430070 China Hubei Key Laboratory of Advanced Technology for Automotive Components Wuhan University of Technology Wuhan430070 China State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Hubei Wuhan430073 China

Estimating the remaining useful life (RUL) of proton exchange membrane fuel cell (PEMFC) is beneficial for deploying control strategies. Long-term aging prediction forms the foundation for RUL estimation, but currently long-term aging prediction and RUL estimation for dynamic load cycling conditions have not been achieved, and uncertainty during the prediction and estimation processes has not been considered. Therefore, in this study, a novel hybrid prediction framework based on Bayesian gated recurrent unit, model uncertainty and state estimation (MUSE), and convolutional neural network-long short-term memory (CNN-LSTM) is proposed. First, MUSE is used to simultaneously quantify the state of health (SOH) and predict aging trend to generate a guiding sequence Next, based on the sequence and historical experimental data, CNN-LSTM is trained and multi-step prediction is performed. Subsequently, Bayesian gated recurrent unit is employed to fuse the MUSE-based prediction sequence with the CNN-LSTM-based prediction, and confidence interval is provided. This results in a novel model and data-driven long-term aging prediction structure. Finally, SOH during the prediction stage is evaluated by MUSE and RUL is estimated. The proposed method is validated using experimental data under a dynamic load cycling condition, demonstrating accurate long-term aging prediction and RUL estimation while considering uncertainty. © 2024

关键词： Convolutional neural networks

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Demonstrations and marketing strategies of hydrogen fuel cell vehicles in China

Demonstrations and marketing strategies of hydrogen fuel cel...

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作者： Han, Weiqun Zhang, Guofang Xiao, Jinsheng Bénard, Pierre Chahine, Richard Hubei Key Laboratory of Advanced Technology for Automotive Components School of Automotive Engineering Wuhan University of Technology Hubei 430070 China Hydrogen Research Institute Université du Québec À Trois-Rivières Trois-Rivieres QC G9A 5H7 Canada

Of the current new energy vehicles aiming to solve global energy depletion and greenhouse gas emission, the hydrogen fuel cell vehicle is well-reputed for its zero emission, high energy efficiency and recyclable energy resources. Recently, many demonstration projects have been established in China to promote the production and marketing of new energy vehicles, to explore their economical, technical and political feasibility and to detect technological flaws and design deficiency. Thus, the paper tends to explore these demonstration projects of hydrogen fuel cell vehicles and their marketing strategies in China. After analysing the significance, history, and pattern of these demonstration projects, the paper reviews various cases such as Beijing Olympic Games, Shanghai World Expo, Guangzhou Asian Games, Shenzhen Universiade and project Thousand New Energy Vehicles in Ten Cities. Finally, after giving some advice on the infrastructure (refuelling station and delivery truck) and marketing strategies, the paper predicts the market prospects of the hydrogen fuel cell vehicle. The paper, as the first elaboration on the relationship between the demonstration and the marketing of the new energy vehicles, comes to the conclusion that the demonstration of the new energy vehicle is an essential process for its exploration and marketing. © 2014, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.

关键词： Fuel cells

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Simulation of hydrogen storage tank packed with metal-organic framework

Simulation of hydrogen storage tank packed with metal-organi...

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作者： Xiao, Jinsheng Hu, Min Bénard, Pierre Chahine, Richard Hubei Key Laboratory of Advanced Technology for Automotive Components School of Automotive Engineering Wuhan University of Technology Hubei 430070 China Hydrogen Research Institute Université du Québec À Trois-Rivières QC G9A 5H7 Canada School of Materials Science and Engineering Wuhan University of Technology Hubei 430070 China

Hydrogen adsorption in high surface metal-organic framework (MOF) has generated significant interest over the past decade. We studied hydrogen storage processes of MOF-5 hydrogen storage systems with adsorbents of both the MOF-5 powder (0.13 g/cm3) and its compacted tablet (0.30 g/cm3). The charge-discharge cycles of the two MOF-5 adsorbents were simulated and compared with activated carbon. The physical model is based on mass, momentum and energy conservation equations of the adsorbent-adsorbate system composed of gaseous and adsorbed hydrogen, adsorbent bed and tank wall. The adsorption process was modeled using a modified Dubinin-Astakov (D-A) adsorption isotherm and its associated variational heat of adsorption. The model was implemented by means of finite element analysis software Comsol Multiphysics™, and the system simulation platform Matlab/Simulink™. The thermal average temperature from Comsol simulation is used to fill the gap between the system model and the multi-dimensional models. The heat and mass transfer feature of the model was validated by the experiments of activated carbon, the simulated pressure and temperatures are in good agreement with the experimental results. The model was further validated by the metal-organic framework of Cu-BTC and is being extended its application to MOF-5 in this study. The maximum pressure in the powder MOF-5 tank is much higher than that in the activated carbon tank due to the lower adsorbent density of MOF-5 and resulting lower hydrogen adsorption. The maximum pressure in the compacted MOF-5 tank is a little bit lower than that in the activated carbon tank due to the higher adsorbent density and resulting higher hydrogen adsorption. The temperature swings during the charge-discharge cycle of both MOF-5 tanks are higher than that of the activated carbon tank. These are caused mainly by pressure work in the powder MOF-5 tank and by adsorption heat in the compacted MOF-5 tank. For both MOF-5 hydrogen storage systems,

关键词： Hydrogen storage

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Influence Law of Different Factors on the Roll Forming Precision of Aluminum Alloy Cylinder with Variable Curvature Section 2

Influence Law of Different Factors on the Roll Forming Preci...

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2nd International Conference on New Materials, Machinery, and Vehicle Engineering, NMMVE 2023

作者： Li, Weihao Song, Yanli Lu, Jue Wang, Xuchu Zhu, Chundong Yang, Lin Hubei Key Laboratory of Advanced Technology for Automotive Components Wuhan University of Technology Wuhan430070 China Hubei Engineering Research Center for Green and Precision Material Forming Wuhan University of Technology Wuhan430070 China China Construction Third BUREAU Third Construction Engineering Co. Ltd Wuhan430074 China

ISBN: (纸本)9781643684208

High precision roll forming of cylinders with variable curvature section is a technical challenge for high-performance manufacturing of oil and gas transportation tanks. In this work, the large cylinder with variable curvature section was taken as the object of study, a four-roll roll bending FE (Finite Element) model of large cylinder with variable curvature section was established to investigate the influence of driving roll speed on the precision of cylinder forming quality, and the influence of adjacent arc segment size on the precision of cylinder roll forming was obtained by the segmental forming simulation of the cylinder. The results show that the forming radius increased sharply after the speed exceeded the threshold value and the main factors of roll forming radius error is the radius and length of the front arc, the radius and length of the middle arc, and the radius and length of the rear arc. © 2023 The authors and IOS Press.

关键词： Aluminum alloys

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Sensitivity analysis on the finance subsidies of regular bus to residents' traveling choice

Sensitivity analysis on the finance subsidies of regular bus...

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International Conference on Transportation Information and Safety (ICTIS)

作者： Shunxi Li Liying Lu Chaozhong Wu Ming Zhong Hubei Key Laboratory of Advanced Technology for Automotive Components Wuhan University of Technology Ministry of Education Wuhan University of Technology

In order to clarify the impact of financial subsidies on residents' travel choice, the paper used the method of multivariate logistic regression to establish residents travel mode choice. And cost-effectiveness analysis was carried out on the traveling choice of bus, with the benefit cost ratio instead of the benefit function in traditional logit model. Taking Beijing for case study, the paper calculates Beijing's current situation both with the unmodified and modified logit model, with the probability of residents choosing bus travel increasing from 31.52% to 41.95%. It shows that modified logit model is more accurately described the actual residents travel choice, other than that, to improve the benefit cost ratio of traveling by bus through subsidies. The finding can be used to increase the probability of residents choosing bus travel by using the way of fiance subsidies, and finally to ease the city's public transportation problem.

关键词： Safety Economics Indexes Analytical models Probability

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Research On The Mechanical Property and Microstructure of Pre-Hardened Single Point Incremental Room Temperature Forming of the 2219 Aluminum Alloy

SSRN

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SSRN 2023年

作者： Hu, Zhili Li, Yan Pang, Qiu Hubei Key Laboratory of Advanced Technology of Automobile Components Wuhan University of Technology Wuhan430070 China Hubei Longzhong Laboratory Wuhan University of Technology Xiangyang441000 China Hubei Collaborative Innovation Center for Automotive Components Technology Wuhan University of Technology 430070 China Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan University of Science and Technology Wuhan430081 China

Single point incremental forming is a flexible and fast sheet metal processing process without a die that is adapted to the processing of small parts in single pieces. Soft state (O state) high-strength aluminum alloy sheet is often used for single-point incremental forming, and then solution-quenching-aging heat treatment is carried out to obtain high strength (T6 state) after forming. However, the heat treatment will lead to poor precision, requiring repeated manual shape calibration, resulting in a long process with low efficiency and a high cost. This paper presents a novel pre-harden single point incremental room temperature forming process of the 2219 aluminum alloy. The sheet is first pre-aged to a hardened state, and after forming, high strength and high precision components can be obtained without further heat treatment. The tensile behavior of the pre-aged alloy is studied by tensile tests, the temperature during the forming process is characterized by thermal imaging, the mechanical properties after forming is evaluated by the hardness tester, the stress-strain and temperature evolution during the forming process are analyzed by numerical simulation, and the microstructure evolution during the process is characterized by transmission electron microscopy (TEM). The results show that the hardness of the parts obtained from this new process reaches up to 140 HV, which exceeds that of the traditional T6 state (125 HV). The large number of dislocations generated during single-point incremental forming not only increases the hardness but also lowers the precipitation temperature of the strengthening phase θ', and the frictional heat generated during the forming process promotes the large precipitation of the θ' phase. The process greatly improves the forming efficiency and ensures the mechanical properties, and it can be applied to the production of various parts. © 2023, The Authors. All rights reserved.

关键词： Room temperature

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Effect of Topology Structure on the Output Performance of an automobile Exhaust Thermoelectric Generator

Effect of Topology Structure on the Output Performance of an...

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2017 2nd Asia Conference on Power and Electrical Engineering (ACPEE2017)

作者： W Fang S H Quan C J Xie B Ran X L Li L Wang Y T Jiao T W Xu Hubei Key Laboratory of Advanced Technology for Automotive Components Automobile Engineering Institute Wuhan University of Technology School of Automation Wuhan University of Technology Department of Civil & Environment Engineering University of Wisconsin

The majority of the thermal energy released in an automotive internal combustion cycle is exhausted as waste heat through the tail pipe. This paper describes an automobile exhaust thermoelectric generator(AETEG), designed to recycle automobile waste heat. A model of the output characteristics of each thermoelectric device was established by testing their open circuit voltage and internal resistance, and combining the output characteristics. To better describe the relationship, the physical model was transformed into a topological model. The connection matrix was used to describe the relationship between any two thermoelectric devices in the topological structure. Different topological structures produced different power outputs;their output power was maximised by using an iterative algorithm to optimize the series-parallel electrical topology structure. The experimental results have shown that the output power of the optimal topology structure increases by 18.18% and 29.35% versus that of a pure in-series or parallel topology, respectively, and by 10.08% versus a manually defined structure(based on user experience). The thermoelectric conversion device increased energy efficiency by 40% when compared with a traditional car.

关键词： Effect of Topology Structure on the Output Performance of an automobile Exhaust Thermoelectric Generator

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Research on the Thermal Management Control Strategy of Electric Vehicles Based on the Soft Actor-Critic Algorithm

SSRN

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SSRN 2024年

作者： Yuan, Xiao-Hong Sun, Zhuo-Song Su, Chu-Qi Wang, Yi-Ping Liu, Xun Hubei Key Laboratory of Advanced Technology for Automotive Components Wuhan University of Technology Wuhan China Hubei Collaborative Innovation Centre for Automotive Components Technology Wuhan University of Technology Wuhan China

This paper presents a thermal management control strategy for electric vehicles that utilizes the Soft Actor-Critic (SAC) algorithm, a form of deep reinforcement learning. The paper commences with a comprehensive introduction and analysis of the thermal management system and heat load of electric vehicles. Subsequently, a controller based on the SAC algorithm was designed and trained. The controller guarantees battery safety and cabin comfort while optimizing energy efficiency. A series of simulation experiments are presented to demonstrate the effectiveness of a control strategy based on deep reinforcement learning for thermal management in electric vehicles. The experimental results indicate that the SAC controller outperforms rule-based controllers. The findings suggest that this SAC-based control strategy could be a novel and effective solution for thermal management in electric vehicles. © 2024, The Authors. All rights reserved.

关键词： Reinforcement learning

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Mppt Design of Centralized Thermoelectric Generation System Under Non-Uniform Temperature Distribution Based on Coot Optimization Algorithm

SSRN

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SSRN 2023年

作者： Yuan, Xiao-Hong Li, Bo Liu, Xun Xiong, Xin Wang, Yi-Ping Hubei Key Laboratory of Advanced Technology for Automotive Components Wuhan University of Technology Wuhan China Hubei Collaborative Innovation Centre for Automotive Components Technology Wuhan University of Technology Wuhan China

Due to the fact that thermoelectric generation (TEG) systems commonly operate in environments where temperature distribution is non-uniform, consequently the output characteristic curve P-V for centralized TEG systems gives rise to several local maximum power points (LMPP). The paper suggests a COOT algorithm-based maximum power point tracking (MPPT) method for centralized TEG systems that can detect the global maximum power point (GMPP).The algorithm is optimized by imitating the collective behavior of Coot water birds, which involves their leadership structures and chain movements, to enhance its capability of jumping out the local optima. To evaluate its performance, this paper conducted distinct case studies that included engine speed at 1000, 2500, and 4000 rpm, step changes and randomly changes. The COOT algorithm's effectiveness was evaluated by comparing its performance with that of traditional Perturbation and Observation (P&O) as well as with the meta-heuristic algorithms Grey Wolf Optimisation (GWO) and Particle Swarm Optimisation (PSO) algorithms. It is shown that the COOT algorithm can achieve optimum power output and effectively reduce fluctuations in output power, while converging to the optimal solution more quickly. © 2023, The Authors. All rights reserved.

关键词： Temperature distribution

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