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Differentiated Allocation Model of Renewable Energy Green Certificates for New-Type Power System ZHANG Shuo, LI Wei, LI Yingzi, LIU Qiang, ZENG Ming Journal of Shanghai Jiao Tong University    2022, 56 (12): 1561-1571.   DOI: 10.16183/j.cnki.jsjtu.2022.150 Accepted: 24 October 2022 Abstract （897）   HTML （785）    PDF （1436KB）（486）       Knowledge map    In order to achieve China’s “30·60” decarbonization goal, the green and low-carbon transformation of the energy system is the fundamental support; the construction of new-type power system is the key step, and the green certificate is the important voucher to reflect the green value of renewable energy. Currently, the distribution mechanism of green certificates in China is oversimplified, which neither effectively measures the variability of green values generated by different types of renewable energy, nor balances the coordinated development of renewable energy. Therefore, to differentiate the exchange mechanism of green certificates by different types of renewable energy power in this paper, an evaluation index system is established, which describes the difference between green certificates, considering the comprehensive value of renewable energy, and an evaluation model is built with the criteria importance by using the intercriteria correlation (CRITIC) method, the entropy weight method, and the technique for order preference by similarity to an ideal solution (TOPSIS) method. Under the development scenario of peaking carbon emissions before 2030, the impact of the differentiated distribution model on the green incomes of centralized photovoltaic distributed photovoltaic power, onshore wind power, and offshore wind power is analyzed. Moreover, the development plan of renewable energy is modified in consideration of the effect of the differentiated distribution model, and policy suggestions on green certificates are proposed accordingly. The results show that the differentiated distribution model of green certificates is practical to provide corresponding decision-making support to the construction and improvement of green certificates trading mechanism in China. Table and Figures | Reference | Related Articles | Metrics

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Linear Parameter-Varying Integrated Control Law Design for a Hypersonic Vehicle YANG Shu, QIAN Yunxiao, YANG Ting Journal of Shanghai Jiao Tong University    2022, 56 (11): 1427-1437.   DOI: 10.16183/j.cnki.jsjtu.2022.190 Accepted: 05 September 2022 Abstract （681）   HTML （350）    PDF （2903KB）（395）       Knowledge map    A linear parameter-varying (LPV) integrated control law is designed for a hypersonic vehicle to achieve trajectory control based on an altitude-horizontal trajectory control concept. The LPV output-feedback control theory and pole placement techniques are employed to design parameters of the control law within a Mach number envelope. Such a control law performs integrated control for longitudinal and lateral-directional dynamics of the vehicle, free from the scheme of inner and outer control loops of classical flight controls and ensuring robust and optimal control performance in the sense of L2-induced norm. A mathematical model of the hypersonic vehicle is developed in the Earth-centered-Earth-fixed reference frame. Earth rotation, Earth oblateness, and the second order harmonic perturbations of Earth are considered in the model. Numerical simulations are conducted to examine the performance of the LPV controller. The simulation results indicate that the closed-loop system of the hypersonic vehicle achieves D-stability. The LPV control law achieves a good performance in vehicle trajectory control and has sufficient robustness with respect to perturbations and sensor noise. Table and Figures | Reference | Related Articles | Metrics

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Inertial Control Strategy for Wind Farm with Distributed Energy Storage System Based on Model Predictive Control SHEN Yangwu, SONG Xingrong, LUO Ziren, SHEN Feifan, HUANG Sheng Journal of Shanghai Jiao Tong University    2022, 56 (10): 1285-1293.   DOI: 10.16183/j.cnki.jsjtu.2022.134 Accepted: 19 May 2022 Abstract （661）   HTML （1092）    PDF （1641KB）（467）       Knowledge map    Distributed energy storage (DES) wind turbine is an effective means to solve the problem of system frequency stability caused by large-scale wind power connection. In this paper, an inertial control method for DES wind farms based on model predictive control (MPC) is proposed.First, the linearized prediction model of the DES wind farm is established. Then, on this basis, in combination with the control framework of MPC, an optimization model and strategy of MPC inertial control are proposed considering the cost of energy storage loss and the balanced change of wind turbine rotor speed,in order to achieve the balanced change of wind turbine rotor speed during inertia control. The simulation results show that the proposed control strategy can effectively coordinate the active power output of the wind power generation unit and the energy storage system unit in the DES wind turbine, reduce the cost of charging and discharging loss of the energy storage system, and ensure that the rotational speed of all wind turbines in the wind farm tends to be average during the inertial control period, avoiding the problem of wind turbines exiting frequency regulation due to excessive reduction of the rotational speed of wind turbines. The inertial control strategy of the DES wind farm is beneficial to improve the frequency stability of the power grid, which is of great significance to ensure the safe operation of the power grid. Table and Figures | Reference | Related Articles | Metrics

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“Window Effect” and Protective Measures of Exogenous Pulsed Electromagnetic Field on Implantable Cardiac Pacemaker LU Wu, DING Ranran, ZHAO Wenbin, HUANG Dong, WANG Zheming Journal of Shanghai Jiao Tong University    2022, 56 (11): 1518-1531.   DOI: 10.16183/j.cnki.jsjtu.2021.326 Abstract （606）   HTML （5）    PDF （24935KB）（229）       Knowledge map    The electromagnetic interference (EMI) from pulsed electromagnetic field (PEMF) on pacemakers is unignorable in modern power grids and healthcare environments, but there is limited study on the interaction mechanisms and protective measures. In this paper, an in-vitro human chest model for pacemaker implantation is made by using pork tissues immersed in 0.9% sodium chloride solution. The effect of PEMFs generated by the switching actions of common electrical equipment and low-frequency medical equipment on pacemakers is simulated by using fast-front current sources. The pulse forming line theory is employed for analyzing the waveform compression of PEMFs in human thoracic cavity. Further, the parameterized bio-electromagnetic transient model of pacemaker in combination with biological tissues is established in finite element software. The results show that pacemaker malfunctions including pacing inhibition and P pulmonale occur under PEMF. The “Window effect” in subcutaneous pouch under PEMF is found by changing the winding of pacemaker leads in the pouch. Based on the research finding, a protective strategy by using composite materials to shield the window area is proposed. The theoretical feasibility of this protective measure is confirmed by simulation, where the intensity of pacemaker EMI could be reduced by 80 dB when the composite materials shielding is used. Finally, a safe distance is developed for pacemaker wearers in electrical and medical environments. Table and Figures | Reference | Related Articles | Metrics

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Peafowl Optimization Algorithm Based Bi-Level Multi-Objective Optimal Allocation of Energy Storage Systems in Distribution Network YANG Bo, WANG Junting, YU Lei, CAO Pulin, SHU Hongchun, YU Tao Journal of Shanghai Jiao Tong University    2022, 56 (10): 1294-1307.   DOI: 10.16183/j.cnki.jsjtu.2021.371 Abstract （580）   HTML （202）    PDF （2519KB）（287）       Knowledge map    Based on the relation between battery energy storage systems (BESSs) planning and operation, a multi-objective optimal allocation model that takes into account both economic and technical requirements is established, and a bi-level optimization structure is constructed to ensure effective planning and high-efficient operation of BESSs. In the inner layer, a peafowl optimization algorithm (POA) is employed to solve the BESSs charge-discharge operation strategy with the purpose of BESSs operation benefit maximization. In the outer layer, a multi-objective peafowl optimization algorithm (MOPOA) is devised to solve the Pareto solution set of BESSs siting and sizing scheme, which aims at minimizing BESSs cost, as well as voltage fluctuation and load fluctuation in distribution network. Furthermore, a typical scenario set is obtained via the clustering algorithm considering uncertain operating conditions. The simulation is performed based on the extended IEEE-33 bus system. The results show that the proposed algorithm achieves a trade-off between local search and global search, thus obtains a high-quality solution. It can obtain a more widely distributed and uniform Pareto front, which not only achieves the best investment benefit, but also improves voltage quality and power stability. Table and Figures | Reference | Related Articles | Metrics

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Cooperative Navigation of UAV Formation Based on Relative Velocity and Position Assistance GUO Pengjun, ZHANG Rui, GAO Guangen, XU Bin Journal of Shanghai Jiao Tong University    2022, 56 (11): 1438-1446.   DOI: 10.16183/j.cnki.jsjtu.2022.232 Accepted: 05 September 2022 Abstract （567）   HTML （25）    PDF （1260KB）（297）       Knowledge map    Because the navigation errors of inertial navigation system accumulate with time, the unmanned aerial vehicle (UAV) formation that only relies on inertial navigation system for positioning cannot obtain precision navigation information in long time flight. To solve this problem, this paper proposes a cooperative navigation scheme for master-slave UAV formation. First, the UAV is equipped with relative navigation sensors to measure the relative velocity and position information between the members of the master-slave UAV formation. Then, considering the relative pose of formation members, the spatial unified transformation scheme is studied. The absolute navigation information measured by each member of UAV formation by inertial navigation system and the relative navigation information measured by relative sensors is unified into the same navigation coordinate system. Finally, a cooperative navigation scheme based on relative velocity and relative position assistance is given. The 30 min simulation results show that the speed and position errors of each cluster converge to 0.1 m/s and 5 m respectively under this scheme, which is more suitable than the inertial navigation system. Table and Figures | Reference | Related Articles | Metrics

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A Sensing Method Based of Floating Photovoltaic Grids to Sudden Changes in Marine Weather JIANG Haoyu, WANG Peilun, GE Quanbo, XU Jinqiang, LUO Peng, YAO Gang Journal of Shanghai Jiao Tong University    2022, 56 (12): 1584-1597.   DOI: 10.16183/j.cnki.jsjtu.2021.526 Abstract （538）   HTML （191）    PDF （8866KB）（290）       Knowledge map    Currently, the application of floating photovoltaics in the ocean is mainly restricted by the cost of submarine cables and special buoys. It will show a high degree of applicability if the energy is consumed by the unmanned management systems on ocean farms and in other scenarios. The grid system formed by the floating photovoltaics can satisfy the early warning requirements of the sudden weather changes on ocean farms. Due to the strong follow-up of the photovoltaic output model to random weather changes, based on the spatial-temporal correlation analysis of large-area photovoltaics, hardware, distance, time delay, and weather, a similar power station fusion estimation relationship is established. Based on the long short-term memory (LSTM) algorithm, the ultra-short-term prediction value of the time sequence tracking of similar power stations can be used to estimate the early warning of the status of target similar power stations. The city-scale data was used to verify the feasibility of the proposed idea, which shows that the framework can complement traditional research deficiencies. Table and Figures | Reference | Related Articles | Metrics

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Loop Closure Detection Method of Laser SLAM Based on Global Feature Descriptor HAN Chao, CHEN Min, HUANG Yuhao, ZHAO Minghui, DU Qiankun, LIANG Qinhua Journal of Shanghai Jiao Tong University    2022, 56 (10): 1379-1387.   DOI: 10.16183/j.cnki.jsjtu.2021.202 Abstract （538）   HTML （71）    PDF （5130KB）（281）       Knowledge map    To solve the problem that localization error of the underground inspection system continues to accumulate over time, a loop closure detection algorithm based on point cloud global feature descriptor is proposed, which is suitable for laser simultaneous localization and mapping (SLAM). The feature vector of each point in point cloud is calculated by curvature, then the global feature descriptor of point cloud is constructed based on the angle distribution and scale distribution relationship between the feature vector and center point coordinate system. In addition, the pose transformation of two similar frames is calculated by feature point registration to improve computing efficiency. The proposed algorithm is verified by simulation experiments and open-source data experiments. The experimental results show that the proposed algorithm has a significant improvement in localization accuracy and real-time performance, which can effectively solve the problems of increased cumulative error and poor global consistency of the localization algorithm during long-term inspections. Table and Figures | Reference | Related Articles | Metrics

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Control of Unmanned Aerial Vehicle Based on Gain Adaptive Super-Twisting Sliding Mode Theory ZHOU Qixian, WANG Yin, SUN Xuean Journal of Shanghai Jiao Tong University    2022, 56 (11): 1453-1460.   DOI: 10.16183/j.cnki.jsjtu.2022.238 Accepted: 08 September 2022 Abstract （531）   HTML （11）    PDF （1184KB）（254）       Knowledge map    In this paper, a nonlinear control method is proposed based on the framework of gain adaptive sliding mode control to deal with the attitude control problem of an unmanned aerial vehicle (UAV), which shows a strong robustness with respect to dynamical uncertainties and external disturbance. In the proposed method, an adaptive gain schedule scheme is proposed to deal with dynamical uncertainties while suppressing the chattering in the sliding mode control. First, the UAV model is introduced and its mathematical model is given. Then, the error is used as the state variable to design a stably converging sliding mode surface, and the gain adaptive super-twisting sliding mode (ASTSM) algorithm is used to design a UAV attitude controller that can converge in finite time, and the stability of the closed-loop UAV system is demonstrated by the Lyapunov’s second method. Finally, the efficiency of the proposed method is demonstrated through comparative simulations. Table and Figures | Reference | Related Articles | Metrics

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Analysis of Sub/Super-Synchronous Oscillation of Direct-Drive Offshore Wind Power Grid-Connected System via VSC-HVDC ZHANG Zhiqiang, LI Qiutong, YU Hao, CHEN Honglin, SUN Haishun Journal of Shanghai Jiao Tong University    2022, 56 (12): 1572-1583.   DOI: 10.16183/j.cnki.jsjtu.2021.434 Accepted: 24 October 2022 Abstract （526）   HTML （84）    PDF （10512KB）（253）       Knowledge map    The system of offshore direct-drive wind farm connected to the power grid via voltage source converter based high voltage direct current (VSC-HVDC) transmission consists of several converters, which have different time scale control loops and complex dynamic characteristics. Based on an example case with two direct-drive wind farms and VSC-HVDC transmission system, the sub/super-synchronous oscillation modes of the system and its relationship with current control loops are studied by state space analysis. The research shows that there are three dominant modes related to the current control of the converter in the system, which are the oscillation mode between wind farms and the offshore converter station, the mode between the offshore wind farms, and the mode between the onshore converter station and the alternating current (AC) system. The modes at the wind farm side are decoupled from the mode between the onshore converter station and the AC system. The relevant control parameters of the converters and the operating conditions have an important impact on the stability of the three modes. The oscillation caused by the single dominant mode may spread to the other side of VSC-HVDC, which means it is necessary to identify the root cause of oscillation in order to design the suppression strategy. The research results is of guidance to the understanding of the dynamic characteristics of offshore wind power grid-connected systems via VSC-HVDC, parameter design, and oscillation suppression. Table and Figures | Reference | Supplementary Material | Related Articles | Metrics

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Prediction of Modulus of Composite Materials by BP Neural Network Optimized by Genetic Algorithm WANG Zhuoxin, ZHAO Haitao, XIE Yuehan, REN Hantao, YUAN Mingqing, ZHANG Boming, CHEN Ji’an Journal of Shanghai Jiao Tong University    2022, 56 (10): 1341-1348.   DOI: 10.16183/j.cnki.jsjtu.2021.126 Accepted: 28 June 2022 Abstract （509）   HTML （125）    PDF （2532KB）（336）       Knowledge map    In order to reduce the cost of testing and shorten the design cycle, this paper studies the prediction method of the modulus of resin matrix composites based on the machine learning method. Using a new prediction method — the neural network in combination with the genetic algorithm (GA-ANN), the strength, the Poisson’s ratio, and the failure strain of the T800/epoxy composite material are used as three input variables of the back propagation (BP) neural network. Then, the optimal threshold and weight are obtained in the genetic algorithm (GA), which are assigned to the corresponding network parameters, and the BP neural network is updated for higher accuracy to predict the modulus of resin matrix composites. Under the same conditions, the Adam algorithm is used to predict. A comparison of these two methods fully proves the feasibility of the GA-ANN algorithm. Table and Figures | Reference | Related Articles | Metrics

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Intelligent Bearing Fault Diagnosis Based on Adaptive Deep Belief Network Under Variable Working Conditions MA Hangyu, ZHOU Di, WEI Yujie, WU Wei, PAN Ershun Journal of Shanghai Jiao Tong University    2022, 56 (10): 1368-1377.   DOI: 10.16183/j.cnki.jsjtu.2021.161 Accepted: 11 July 2022 Abstract （491）   HTML （103）    PDF （7932KB）（286）       Knowledge map    In engineering, working environment and operating state are constantly changing, which decreases the correct rate of equipment fault diagnosis, resulting in the loss of time and cost. The structure of the deep belief network is investigated for the time-varying factors in the mechanical system. In combination with the signal decomposition technology of fixed learning step size, the original characteristics of the sensor data are retained. In addition, the deep key information of the signal is repeatedly extracted layer by layer. The data loss technology is integrated to optimize the network structure to avoid over-fitting problems. Further, considering the domain adaptive method in transfer learning, the memory characteristics of different levels of deep belief networks are solidified. Therefore, a domain adaptive deep belief network with shift-invariant features (SIF-DADBN) is proposed for rolling bearing fault diagnosis. By identifying the characteristic information of similar fault signals with variable working conditions, the accuracy and generalization of bearing intelligent fault diagnosis are both improved. Based on the public data set of rolling bearings, the average correct rate of the fault diagnosis technology is found to be as high as 95.65%. Compared with five other methods, the effectiveness and accuracy of SIF-DADBN under variable working conditions are verified. Table and Figures | Reference | Related Articles | Metrics

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Dual Modular Soft Robot with Multi-Terrain Movement Ability WANG Yuxuan, LIU Zhaoyu, WANG Jiangbei, FEI Yanqiong Journal of Shanghai Jiao Tong University    2022, 56 (10): 1388-1396.   DOI: 10.16183/j.cnki.jsjtu.2021.290 Abstract （489）   HTML （83）    PDF （32108KB）（291）       Knowledge map    Aimed at the problems of limited application range, single movement scene, inability of climbing, and limited space movement of the multi-terrain movement robot, a novel dual module soft robot with the multi-terrain movement ability is proposed. Each soft module is composed of a four-chamber omnidirectional bending soft pneumatic actuator. By establishing the bending model of the omnidirectional bending soft actuator, the variation law of the omnidirectional bending soft actuator is analyzed. A new rotary movement mode is proposed, which enables the robot to move in a variety of complex environments in the rotary movement mode. A gait control method based on pulse width modulation (PWM) is proposed to make the robot realize the multi-terrain movement function more simply and quickly, and its feasibility is verified by experiments. The experimental results show that the dual modular soft robot based on the four-chamber omnidirectional bending soft actuator can climb vertically along circular pipes, square pipes, and irregular rods (human forearms), and the crawling speed can reach 11.7 mm / s. It can also move rapidly in complex terrain such as flat ground, artificial turf, rugged road surface, and slope, and the crawling speed can reach 14.0 mm/s, which overcomes the shortcomings of the existing pipe climbing robot and multi-terrain movement robot. The modular soft robot can move stably and quickly in a variety of terrain, and has a strong adaptability. It has a potential application value in pipeline detection and complex terrain detection. Table and Figures | Reference | Related Articles | Metrics

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Two-Stage Optimal Schedule of Offshore Wind-Power-Integrated Multi-Microgrid Considering Uncertain Power of Sources and Loads LU Qiuyu, YU Zhen, YANG Yinguo, LI Li Journal of Shanghai Jiao Tong University    2022, 56 (10): 1308-1316.   DOI: 10.16183/j.cnki.jsjtu.2021.409 Abstract （487）   HTML （223）    PDF （1391KB）（233）       Knowledge map    Considering the high-randomness and the low-economic-benefit characteristics of the offshore wind-power-integrated multi-microgrid, a two-stage optimal scheduling method considering the uncertain power of source and load is proposed to improve the operation profits of offshore wind-power-integrated multi-microgrid. The proposed two-stage optimal scheduling method consists of a day-ahead stage and an hour-ahead stage. In the day-ahead stage, the proposed method is based on the forecast data of the wind power and the load demand, which considers the distribution characteristics of the prediction errors. A stochastic optimization model is established to determine the unit committee of the diesel generators and the state-of-charge of the battery storages, so as to maximize the expected daily operation income. A deterministic optimization model is established based on the decisions from the day-ahead optimization relying on the hour-ahead forecast data of the wind power output and load demand. By optimizing the power of the diesel generators, wind turbines and battery energy storages, the operation income of each hour is maximized. Finally, a simulation model is established to verify the proposed method based on the prediction data of sources and loads in wind-power-integrated multi-microgrid. The simulation results show that compared with the conventional schedule strategies, the proposed two-stage optimal scheduling method can achieve a higher income and a higher overall consumption rate of the wind power. Table and Figures | Reference | Related Articles | Metrics

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High Performance Capacitors Based on Graphene and Boron Nitride WU Jing, TAN Haiyun, SHI Yuchao, HOU Weihong, TANG Ming Journal of Shanghai Jiao Tong University    2022, 56 (10): 1325-1333.   DOI: 10.16183/j.cnki.jsjtu.2021.188 Abstract （484）   HTML （167）    PDF （9999KB）（272）       Knowledge map    Flexible all-solid-state supercapacitors (FASS) are energy supplies for wearable electronic devices and power devices. Graphene nanosheets have unique two-dimensional (2D) structures, strong mechanical properties, and an excellent electrical conductivity, which are widely used in paper-like flexible electrodes. The essential feature of the double-layer electric performance for the simple graphene nanosheet-based FASS restricts the improvement of their capacitive performance and practical applications. FASS based on the ultralarge graphene nanosheets and the ultrathin boron nitride (BN) nanosheets are investigated. The nacre-like structures could efficiently integrate both merits of pseudocapacitive BN nanoflakes and conducting graphene, thereby exhibiting an excellent electrochemical performance in FASS. After 5000 charge-discharge cycles, the highest areal specific capacitance of FASS reaches 325.4 mF/cm2, with a high capacity retention rate of about 86.2% and a high energy density of 22.8 W·h/kg (1 W·h=3.6 kJ) at a power density of 85.7 W/kg. Table and Figures | Reference | Related Articles | Metrics

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Resistance Element Welding of Carbon Fiber Reinforced Thermoplastic Composites to High-Strength Steel WANG Yecheng, LI Yang, ZHANG Di, YANG Yue, LUO Zhen Journal of Shanghai Jiao Tong University    2022, 56 (10): 1349-1358.   DOI: 10.16183/j.cnki.jsjtu.2021.271 Accepted: 08 April 2022 Abstract （468）   HTML （135）    PDF （47715KB）（324）       Knowledge map    The high strength joining of carbon fiber reinforced nylon 6 composites (CF/PA6) to TWIP980 steel was achieved by resistance element welding (REW). A 304 stainless steel rivet was used as an assistant element. The effect of welding current and welding time on the joint mechanical property was studied. Four joint failure modes with different strengths were identified, and the microstructures of joints, and the interfaces between CF/PA6 and the steel were analyzed. As the melting point and thermal conductivity of CF/PA6 are lower than those of the high-strength steel, it is prone to overheat and decompose during welding. While ensuring the formation of a certain size of weld nugget, avoiding or reducing the decomposition of CF/PA6 is the key to the successful implementation of CF/PA6 high-strength steel REW. By using a hard welding process such as high welding current and short welding time, high strength joints can be obtained while reducing the decomposition of CF/PA6. Based on the failure load of the joint, the weld lobe under the conditions of this study was determined. The process is sensitive to the change of welding time, and the allowable welding time range is narrow. The decomposition of CF/PA6 cannot be avoided completely even when the welding parameters in the weld lobe are employed. Therefore, it is necessary to conduct further research on the temperature field and the nugget formation mechanism of the REW process. Table and Figures | Reference | Related Articles | Metrics

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A Sliding Window Adaptive Filtering Algorithm for Autonomous Navigation of the Approach Phase of Deep Space Probe ZHANG Wenjia, MA Xin Journal of Shanghai Jiao Tong University    2022, 56 (11): 1461-1469.   DOI: 10.16183/j.cnki.jsjtu.2022.233 Accepted: 05 September 2022 Abstract （461）   HTML （6）    PDF （2984KB）（213）       Knowledge map    When the deep space probe approaches the target planet, due to the rapid increase of the gravity of the target planet, the orbital dynamics model will have a rapid acceleration change. Because the noise covariance is not completely known, the traditional filtering algorithm cannot obtain the optimal estimation of navigation parameters, which is difficult to meet the performance requirements of the approach navigation system. In order to meet the requirements of high stability and accuracy of the system, a sliding window adaptive nonlinear filtering algorithm based on system noise covariance is proposed. By constructing the system noise covariance update function and using the sliding window to smooth the noise covariance, the errors caused by velocity noise and position noise are separated, the filter parameter information used is updated in real time, and the system noise covariance is adjusted adaptively. Taking the Mars probe as an example, the simulation results show that, compared with the traditional unscented Kalman filtering method, the position accuracy and velocity accuracy of the proposed method are improved by 90.97% and 66.17% respectively, which suppresses the rapidly changing integral error on the system model, and solves the divergence problem of the traditional filtering method. In addition, the influence of filtering period and window size on navigation performance is analyzed, which provides a feasible new adaptive filtering method for autonomous navigation of deep space exploration. Table and Figures | Reference | Related Articles | Metrics

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Management and Optimal Control Algorithm for Electric Vehicle Charging in Random Environment LIU Didi, YANG Yifei, YANG Yuhui, ZOU Yanli, WANG Xiaohua, LI Xin Journal of Shanghai Jiao Tong University    2023, 57 (1): 1-9.   DOI: 10.16183/j.cnki.jsjtu.2021.499 Accepted: 31 October 2022 Abstract （451）   HTML （251）    PDF （1627KB）（355）       Knowledge map    With the increasing scale of electric vehicles (EVs), the adaptive management of its charging behavior becomes an urgent problem to be solved. From the point of view of charging service provider, an online management algorithm for EV charging is proposed based on the Lyapunov optimization theory under the random environment in this paper, considering renewable sources energy, storage equipment, time-varying electricity price, and the tolerable delay of EV, with an aim of maximizing the benefits of charging service providers (i.e., minimizing the cost of electricity purchased). The performance of the proposed algorithm is analyzed to verify that it can achieve near-optimal optimization results without any a priori statistical information about the system inputs (renewable energy generation, charging demand, and time-varying electricity price). The simulation results show that the proposed algorithm can effectively reduce the economic cost by 27.3% compared with the benchmark algorithm. Table and Figures | Reference | Related Articles | Metrics

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Analysis of Entry Footprint Based on Pseudospectral Method LI Zhaoting, ZHOU Xiang, ZHANG Hongbo, TANG Guojian Journal of Shanghai Jiao Tong University    2022, 56 (11): 1470-1478.   DOI: 10.16183/j.cnki.jsjtu.2022.256 Abstract （450）   HTML （3）    PDF （1383KB）（226）       Knowledge map    Entry footprint is an essential manifestation of vehicle maneuverability, which can provide the basis for trajectory planning and guidance, landing point selection, etc. A fast footprint-generation method based on the pseudospectral method is proposed. The influencing factors of footprint are simulated and analyzed. In this method, the attack and bank angles are simultaneously discretized as control quantities to form the nonlinear programming problem of the pseudospectral method, and the footprint is obtained by solving the maximum transverse range problem for several different longitudinal conditions. Moreover, the affecting factors of the footprint are studied. The simulation results show that the mass, reference area, atmospheric density, etc., do not cause the change of the footprint within a specific range. Beyond a certain range, the short longitudinal trajectory would be significantly affected. The left half of the footprint is affected, while the right half is not changed. The effect of the lift-to-resistance ratio on the footprint is significant, and its size is positively related to the footprint range. Table and Figures | Reference | Related Articles | Metrics

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Working Posture Generation Method for Virtual Human Based on Complete Reachable Region Analysis ZHU Wenmin, LUO Xiaomeng, FAN Xiumin, ZHANG Lei, CAI Junqi Journal of Shanghai Jiao Tong University    2022, 56 (10): 1409-1419.   DOI: 10.16183/j.cnki.jsjtu.2021.304 Accepted: 05 March 2022 Abstract （440）   HTML （59）    PDF （15284KB）（248）       Knowledge map    Due to the large degree of freedom of the human body and the working environment, the generation of virtual human working posture during simulation is very complicated, which requires a lot of time and energy. To solve this problem, according to the structure and motion characteristics of human body, the templates of assembly actions for virtual human are constructed. Through theoretical analysis and calculations, the formulas of the reachable region of different action templates are deduced, and the complete reachable region of the virtual human is established, based on which, feasible assembly actions are screened out through reachability analysis. In combination with the existing multi-objective solution model of virtual human working posture, the automatic generation of virtual human working posture is realized. Based on the above research, this method is verified by examples. Table and Figures | Reference | Related Articles | Metrics