Variable transmission ratio rack is a key component of the variable transmission ratio steering system for new energy vehicles. This paper presents a novel milling method based on the envelope motion between pinion and rack, i.e., generation of variable transmission ratio rack using a multi-axis CNC milling machine tool by a disk cutter. Firstly, the generation relation among virtual generating cross-section, pinion and rack is derived based on the basic concept of generation of variable transmission ratio rack. To establish the cutter geometry, the cutting surface equation of the disk cutter is obtained based on the generation relation. On this basis, the envelope mathematical model of the proposed rack is derived from the cutter geometry by applying coordinate transformation. The kinematic model of a six-axis CNC milling machine tool is further developed and the machine motion parameters during generating milling for variable transmission ratio rack are studied. Finally, a machining simulation of variable transmission ratio rack is carried out via VERICUT software, verifying the feasibility of the milling method. The research makes it possible to process the variable transmission ratio rack with higher tooth surface accuracy.

High-penetration renewable energy grid integration in electric vehicle charging stations and hydrogen refueling stations often faces challenges such as significant energy fluctuations, energy wastage, and system instability. To address these challenges, this study proposes a novel Dynamic Hysteresis Energy Management strategy (DHEM). This strategy incorporates hysteresis theory and adjusts the charge-discharge strategy of the energy storage system by setting thresholds for the State of Charge (SOC) of lithium-ion batteries, namely SOCgrid, SOCelzoff, and SOCelzon. Additionally, a price difference evaluation mechanism is designed for dynamic electricity pricing, optimizing the operation of electrolyzers and batteries, and balancing energy storage and consumption. Multiobjective optimization is subsequently performed using the non-dominated sorting genetic algorithm, focusing on the evaluation of levelized cost of energy (LCOE) and renewable energy wastage. Sensitivity analysis determines the optimal configurations for SOCgrid, SOCelzoff, and SOCelzon within the DHEM. The results demonstrate that compared to traditional and hysteresis-based strategies, the DHEM reduces LCOE by 17% and 11%, respectively. Furthermore, the single-start-stop operation times of Alkaline Electrolyzer and Proton Exchange Membrane Electrolyzer increase by 48% and 12%, and 109% and 14%, respectively. In typical daily operations, DHEM improves system efficiency and stability by optimizing energy storage and power purchase decisions. Additionally, DHEM achieves a balance in cost, environmental, and social benefits, contributing to the sustainable development of electric vehicle charging infrastructure.

Existing research typically optimizes either the thermoelectric leg configuration or the fin structure independently, often neglecting the potential interactions between the two. This study proposes a novel two-stage segmented thermoelectric generator, examining the interplay between thermoelectric legs and fin structure and their impact on energy, exergy, and economic (3E) performance. Using the Taguchi method and Grey Relational Analysis, a joint optimization of thermoelectric legs and fin structure was conducted. The results reveal a significant interaction effect between the leg structure and fin thickness. The optimal leg structure is contingent on the fin thickness, and vice versa. When the area ratio between the upper and lower leg sections is 0.5, the optimal fin thickness is 1 mm; when the area ratio increases to 1, the optimal fin thickness decreases to 0.5 mm. However, the optimal fin spacing is not influenced by the leg structure. The optimized two-stage segmented thermoelectric generator exhibits superior 3E performance, with net power, exergy efficiency, and levelized energy cost reaching 19.36 W, 12.14 %, and 25.5 W/$, respectively. These values represent improvements of 32.3 %, 34.4 %, and 100.7 % over conventional two-stage thermoelectric generators. This study provides crucial design guidance for the joint optimization of fin and thermoelectric semiconductor structures.

Temperature control is crucial for the safety and efficiency of the Proton Exchange Membrane Water Electrolysis (PEMWE) system during continuous operation. This paper focuses on modeling the thermal behavior and designing temperature controllers for a PEMWE system operating under dynamic conditions. A dynamic thermal model of the PEMWE system is developed for simulation and controller design, and its effectiveness is validated using a hardware-in-the-loop simulation platform and real experimental data. Based on this model, an optimized fuzzy PID controller is designed to minimize temperature overshoot. Experimental results indicate that the optimized fuzzy PID controller, compared to traditional PID control, reduces the pump regulation time by approximately 70 seconds and decreases the overshoot by around 4%, resulting in improved control effectiveness. Ultimately, the temperature difference between the electrolyzer inlet and outlet is fine-tuned, the impact of various temperature differences on the PEMWE system is evaluated, and it is recommended to regulate the temperature difference to 3-5°C.

Electrostatic energy storage based on dielectrics is fundamental for high-performance electrical systems. However, developing outstanding energy storage capabilities is challenging because the polarization, loss, and breakdown strength are firmly coupled and mutually restrictive. This work proposes a two-pronged strategy to break out the mutual clamp between these performance parameters by modulating the ergodicity and band structures in Aurivillius ferroelectric films. An inserting layer engineering is carried out using Bi4Ti3O12 as matrix and BiAlO3 as inserting layer. The intrinsic ergodic characteristics drive the realization in the arrangements of internal permanent dipoles through a macroscopically reversible interconversion between relaxor and ferroelectric phases, thereby modulating the pinched double hysteresis loops with both large polarization and low hysteresis. Moreover, the band structure associated with the breakdown strength is additionally regulated by orbital hybridization. Thus, ergodic relaxor ferroelectric film Bi5Ti3AlO15, exhibits an excellent energy storage performance with densities reaching as high as similar to 131.8 J cm(-3) and efficiencies exceeding 73%. This work overcomes the ubiquitous trade-off among polarization, hysteresis, and breakdown strength, offering extra insight into developing dielectric energy storage capacitors.

Considering the impact of adaptation of different power fluctuation frequencies of Hydrogen Energy Storage (HES) and Electric Energy Storage (EES) on system lifetime and system efficiency. In this paper, a multi-objective optimal operation method under power allocation for hydrogen-electric hybrid energy storage system is proposed. First, the historical data of renewable power generation are decomposed into components with different frequencies and scales by Complete Ensemble Empirical Modal Decomposition with Adaptive Noise (CEEMDAN). The Hilbert transform is applied to identify the mixed energy minima composed of the frequency information under different functions, facilitating the identification of the frequency dividing point for determining the high- and low-frequency power components. Then, the constraints under the multi-objective optimization model containing the system operation and performance degradation rate are constructed with the objective of maximizing the system efficiency and system lifetime. For complex operational optimization, Pareto optimal solutions are obtained using non-dominated sorting genetic algorithm-III (NSGA-III). The case study shows that the strategy of H-E HESS proposed in this paper can increase the system energy efficiency by 17.95%, and reduce the degradation rate by 1%. The effectiveness of the strategy is also verified in an experimental platform of an industrial-scale demonstration project.

Enhancing thermoelectric performance hinges on optimizing the geometry of thermoelectric legs. In this study, we present a novel asymmetrical annular thermoelectric generator (ATEG) in which the proportions of P-type and N-type legs are meticulously balanced. We construct a one-dimensional analytical model tailored to this ATEG. Utilizing this model, we derive the relationship governing thermal-electrical impedance matching in an asymmetrical ATEG and formulate a general expression for optimizing the asymmetry coefficient. We explore the influence of various thermal boundary conditions on optimal impedance matching, ideal annular leg parameters, and the optimal asymmetry coefficient. Our findings reveal that thermal boundary conditions significantly affect the optimal load ratio. Furthermore, in comparison to traditional ATEGs, our proposed asymmetrical ATEG with the optimized structure exhibits a remarkable 16.2 % increase in output power while maintaining the same material volume. Additionally, we perform a three-dimensional numerical analysis of the asymmetrical ATEG using Comsol. Our research findings indicate that introducing the asymmetric structure leads to higher maximum thermal stress on the legs. Interestingly, the study of asymmetric thermal boundary conditions highlights that improving heat transfer between the ATEG and the cooler yields higher mechanical reliability compared to enhancing heat transfer between the ATEG and the heat source.

Proton exchange membrane fuel cells (PEMFCs) are essential modern sustainable energy generation devices. Since such an electrochemical system has a limited lifetime, accurately estimating its performance degradation is critical for practical applications. When a large amount of measurement data is available, many nonlinear forecasting methods can be used to predict the performance degradation of a PEMFC system, and the prediction accuracy can be improved by optimizing the structure and parameters of the algorithm. However, the voltage recovery phenomenon would pose a challenge to the classical data-driven methods. In this work, we propose a novel hybrid data-driven PEMFC performance prediction framework by exploring the extensive degradation information buried in the voltage decay data. With complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), the raw voltage data are first decomposed into sequences of multiple time scales. Then, the linear and nonlinear components in the decomposed sequences are predicted by autoregressive integrated moving average (ARIMA) and the attention-based gated recurrent unit (GRU), respectively. Comparative studies show that the proposed method can improve the prediction performance by 42.6%–84.2% on FC1 and 35.0%–90.6% on FC2, compared to state-of-the-art algorithms on the basis of an open-source dataset of PEMFCs.

The conventional methods to improve the performance of annular thermoelectric generators (ATEGs) heavily rely on optimizing the thermal design of individual annular thermoelectric couples (ATECs). However, since a practical ATEG consists of many ATECs, the optimal structure of the ATEG can differ from the ATEC-based design. On the other hand, optimization by simply considering all ATECs can lead to a heavy computation burden. This work first proposes a high-fidelity, fluid-thermal-electric multiphysical ATEG model, solved by a computationally-efficient dual-finite-element method to cope with the challenge. This model explores the effects of ATEC microstructure and heat exchanger structure on ATEG performance under various operating conditions. Comparative multi-objective optimization studies were performed at three levels, i.e., for a single ATEC, a single ring of ATEG, and the entire ATEG. The results reveal that the optimized structural parameters of ATECs have some new features when considering the entire ATEG as the optimization objective. The optimal height, angle, and thickness of ATECs are 12 mm, 2.35 degrees, and 10 mm, respectively. The corresponding net power, efficiency, and power density of ATEG are 321.6 W, 6.58 %, and 634.15 W/m(3), respectively. Compared to the traditional design method based on a single ATEC and a single ring, the net power of the ATEG designed with the proposed method can be enhanced by 168 % and 197 %, respectively, at the expense of only a 20 % reduction in the power density.

The adaptation of annular thermoelectric generator (ATEG) to cylindrical heat sources exhibits a better per-formance compared to widely studied fiat plate type thermoelectric generator (FTEG). To enhance heat transfer and improve the overall performance, a novel structure of the heat exchanger of the twisted-tape annular thermoelectric generator (TT-ATEG) is proposed in this paper. A three-dimensional finite element model of TT-ATEG is established for the first time. The net power gain coefficient and the efficiency gain coefficient are defined to quantify the performance of TT-ATEG, and the gain effects of the length, twist ratio and radius of the twisted tape are analyzed respectively. To maximize the comprehensive performance of TT-ATEG, the optimal weighting factor of net power and efficiency are determined, and the full-parameter optimization of the twisted tape is completed. The results reveal that the optimal performance of TT-ATEG is obtained if the weight ratio of net power and conversion efficiency is 1:4. In our case study, dimensionless factors radius ratio Rr, length ratio Lr and twist ratio of the twisted tape are 0.714, 0.479 and 136.84 respectively. Compared with the ATEG without twisted tape, the net power and efficiency are improved by 10.41% and 22.51%, respectively. The results demonstrate that the novel design of TT-ATEG could accelerate the heat transfer effectively and enhance the overall performance.

As unmanned aerial vehicles (UA V) are widely used in unknown and complex environments, their path planning capabilities face higher requirements. In many cases, UA V cannot obtain the environmental information of the target area in advance, and the reinforcement learning (RL) algorithm to solve this problem faces the problem of slow convergence speed. To solve this problem, a UA V path planning method based on guided Sarsa algorithm is proposed, which defines the return function based on position information and improves the status update strategy. Simulation results show that the proposed method can realize fast path planning of UA V in static environment. Compared with Q learning and unimproved Sarsa algorithm, the obtained path length is shortened by 18 steps and 2 steps. At the same time, after 2000 iterations, only the results obtained by this method have obvious convergence. The convergence speed of guided Sarsa algorithm is relatively accelerated. At the same time, the trajectory tracking process of UA V is realized by MAT LAB platform, which proves the practicability and feasibility of the algorithm.

The variability and randomness of the load bring certain difficulties to the control accuracy of the electromagnet. A novel human-simulation logical control research on liftingelectromagnet is studied in this paper. Based on the pan-Boolean theory, the logical control model for electromagnetic force control system is based on control practice and is consisted by a series of control rules. The dynamic control model of electromagnetic force control system is established in Matlab/Simu1ink, the simulation experimental results show that if adding the human-simulation logical controller, the overshoot of the system is smaller, the response speed is faster, and the steady-state accuracy is higher. The controller can better meet the working requirements of the lifting electromagnet.

电工电子技术基础课程在为理工科大学生传授电气科学知识、培养专业技能的同时,结合双一流建设和新工科发展需要,在课程目标、课程内容组织、课程资源和教学模式上,借助信息化手段将人文素质教育与工程类基础性课程教学有机结合,从而培养学生的人文素养和科学精神.

In this paper, considering the characteristics of the electromagnetic force of the lifting electromagnet in actual production work, a novel electromagnetic force control system for the lifting electromagnet is studied. Based on the Beetle Antennae Search Algorithm (BAS), combined with traditional PID control, the size and direction of the excitation current are controlled in real time by adjusting the IGBT turn-on sequence and turn-on time to achieve rapid adjustment of the magnitude and direction of the electromagnetic force. The simulation experimental results show that if adding the BAS + PID controller, the excitation current overshoot of the system is smaller, the response speed is faster, and the steady-state accuracy is higher. The controller can better meet the working requirements of the lifting electromagnet.

The traditional piezoelectric energy harvester has been used to power to the low-power wireless sensor network node. But its ceramic layer is fragile under the condition of large amplitude, high intensity and long time excitation. In order to solve this problem, the piezoelectric fiber composite MFC acts as a piezoelectric energy harvester. It is more flexible and has a longer service life. The relationship between the output power, energy conversion efficiency of MFC and the load is studied in this paper. The vibration power generation model of the cantilever beam MFC energy absorbing device is established, and the weak energy generated by the MFC energy harvester is collected by the energy collection management chip LTC3588-1. Powering circuit to low-power wireless sensor network node is designed. The experimental results show that there is a certain error between the theoretical and experimental values of the model, but it can reflect the relationship between MFC output power, energy conversion efficiency and load. The cantilever beam MFC energy absorbing device can meet the low power wireless sensing. The power supply of the network node is required.

A piezoelectric generator based on the piezoelectric stacked elements is applied to realize electro- mechanical energy conversion in this paper. The piezoelectric stacked generator is constructed. The relational expression about output electrical characteristic parameters, the constructional dimension parameters of piezoelectric stack elements and external driving forces is discussed here. Theoretical predictions confirmed by experimental results show that the piezoelectric generator produces electrical power with higher efficiency, and energy harvesting circuit can harvest energy from the piezoelectric generator effectively.

The level control system by multi-point real-time detection is designed in this paper based on the fuzzy self-adjusting PID algorithm. It is applied in the non-probe near-field optical microscope. Capacitance-to-digital converter chip AD7746 is used to converted capacitance value which is proportional to the distance between code plate and platform into digital value in the micro-positioning platform. The system has the following advantages such as higher positioning precision, faster response and more stable performance. It can meet the need of the level control precision for micro-motion platform of the non-probe near-field optical microscope. The simulation result indicates that this system may enhance the positioning precision and working efficiency, it is an effective method to realize automatic control in the micro-motion platform. What is more, the control system is simple and practical.

Nano-level current-measuring device is important for the scanning tunneling microscope. The nano-ampere current measuring meter system based on high-precision amplifiers is mainly designed as two-stage amplifiers structure. Some removing interference ways of hardware are introduced in the design and facture of the PCB. In the current-measuring meter system, wavelet transform is adopted to decrease noise. The experiments show that, the measurement results of this device can be obtained to an accuracy of 1 nA, and the device can reduce some noise interference.

In this paper, a kind of Love wave sensors with SiO 2 /36degYX LiTaO 3 structures for monitoring antibody-antigen immunoreactions in aqueous solutions in real time is presented. In this study, the devices with low insertion losses are achieved when the devices are in direct contact with the solutions. In the immunosensing measurements, a goat anti human-immunoglobulin G (HigG) is immobilized on the device surface as a receptor layer for detecting HigG in buffer solution. The results show that the structures have high sensitivity, which demonstrate that the sensors are very effective for biological and chemical sensing applications in liquid environments.