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20 pages, 9992 KiB

Open AccessArticle

A High-Speed Train Traction Motor State Prediction Method Based on MIC and Improved SVR

by Hui Wang, Chaoxu Li, Yuchen Liu and Man Li

Electronics 2024, 13(24), 5036; https://doi.org/10.3390/electronics13245036 - 21 Dec 2024

Viewed by 639

The traction motor realizes the mutual conversion of electrical energy and mechanical energy during the train traction and braking process and is a key component of high-speed trains. The normal operation of the motor is directly related to the safety of high-speed train [...] Read more.

The traction motor realizes the mutual conversion of electrical energy and mechanical energy during the train traction and braking process and is a key component of high-speed trains. The normal operation of the motor is directly related to the safety of high-speed train operation. Changes in temperature signals can reflect faults in the traction motor. By analyzing the internal and external influencing factors of temperature signals, a multi-factor prediction model for traction motors is established based on the maximal information coefficient and improved support vector regression. In this model, highly relevant features selections are performed based on time-delayed sequences and the maximal information coefficient. Using the adaptive particle swarm algorithm to optimize the improved support vector regression algorithm can enhance its accuracy and efficiency. Furthermore, using the K-nearest neighbor algorithm for error prediction will yield more accurate results. By comparing the

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(This article belongs to the Special Issue Recent Advances in Electrified Vehicles and Transportation Electrification)

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18 pages, 21128 KiB

Open AccessArticle

Design and Analysis of a Direct Current–Based Ice Melting System for an Overhead Contact System in Electrified Railways

by Guosheng Huang, Mingli Wu, Guotao Cao, Songping Fu, Xiaojuan Pei, Liran Wu and Qiujiang Liu

Electronics 2024, 13(24), 4871; https://doi.org/10.3390/electronics13244871 - 10 Dec 2024

Viewed by 699

Abstract

In recent years, extremely low-temperature weather conditions have resulted in the formation of ice on the contact network of electrified railways, significantly affecting the security of these systems. To address the issue of icing on the overhead contact system, this paper proposes a [...] Read more.

In recent years, extremely low-temperature weather conditions have resulted in the formation of ice on the contact network of electrified railways, significantly affecting the security of these systems. To address the issue of icing on the overhead contact system, this paper proposes a direct current–based ice melting system. This paper outlines the topological structure of the contact network ice melting system and examines its operational principles. A finite element model was established to investigate the characteristics of the ice melting process on the contact line, and a quantitative analysis was conducted to assess the impact of four critical variables: temperature, ice thickness, direct current, and conductor configuration. Ultimately, a simulation model of the contact line ice melting system for the traction power supply system was developed, and the output/input characteristics of the ice melting system were analyzed to validate its feasibility. Full article

(This article belongs to the Special Issue Recent Advances in Electrified Vehicles and Transportation Electrification)

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17 pages, 542 KiB

Open AccessFeature PaperArticle

Optimal Control of a Semi-Active Suspension System Collaborated by an Active Aerodynamic Surface Based on a Quarter-Car Model

by Syed Babar Abbas and Iljoong Youn

Electronics 2024, 13(19), 3884; https://doi.org/10.3390/electronics13193884 - 30 Sep 2024

Cited by 3 | Viewed by 1459

Abstract

This paper addresses the trade-off between ride comfort and road-holding capability of a quarter-car semi-active suspension system, collaborated by an active aerodynamic surface (AAS), using an optimal control policy. The semi-active suspension system is more practical to implement due to its low energy [...] Read more.

This paper addresses the trade-off between ride comfort and road-holding capability of a quarter-car semi-active suspension system, collaborated by an active aerodynamic surface (AAS), using an optimal control policy. The semi-active suspension system is more practical to implement due to its low energy consumption than the active suspension system while significantly improving ride comfort. First, a model of the two-DOF quarter-car semi-active suspension in the presence of an active airfoil with two weighting sets based on ride comfort and road-holding preferences is presented. Then, a comprehensive comparative study of the improved target performance indices with various suspension systems is performed to evaluate the proposed suspension performance. Time-domain and frequency-domain analyses are conducted in MATLAB^® (R2024a). From the time-domain analysis, the total performance measure is enhanced by about 50% and 35 to 45%, respectively, compared to passive and active suspension systems. The results demonstrate that a semi-active suspension system with an active aerodynamic control surface simultaneously improves the conflicting target parameters of passenger comfort and road holding. Utilizing the aerodynamic effect, the proposed system enhances the vehicle’s dynamic stability and passenger comfort compared to other suspension systems. Full article

(This article belongs to the Special Issue Recent Advances in Electrified Vehicles and Transportation Electrification)

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16 pages, 3987 KiB

Open AccessArticle

MPC-TD3 Trajectory Tracking Control for Electrically Driven Unmanned Tracked Vehicles

by Yuxuan Chen, Jiangtao Gai, Shuai He, Huanhuan Li, Cheng Cheng and Wujun Zou

Electronics 2024, 13(18), 3747; https://doi.org/10.3390/electronics13183747 - 20 Sep 2024

Viewed by 1409

Abstract

To address the trajectory tracking issue of unmanned tracked vehicles, the majority of studies employ the Model Predictive Control (MPC). The MPC imposes high demands on model accuracy. Due to factors such as environmental interference, actuator constraints, and the nonlinearity of vehicles under [...] Read more.

To address the trajectory tracking issue of unmanned tracked vehicles, the majority of studies employ the Model Predictive Control (MPC). The MPC imposes high demands on model accuracy. Due to factors such as environmental interference, actuator constraints, and the nonlinearity of vehicles under high-speed conditions, dynamic and kinematic models fail to accurately delineate the motion process of tracked vehicles. Aiming at the problem of insufficient trajectory tracking precision of unmanned tracked vehicles, a trajectory tracking controller jointly controlled by the Twin Delayed Deep Deterministic policy gradient (TD3) algorithm and the MPC algorithm is developed. During offline training, the agent acquires the discrepancies between the model and the environment under various working conditions and optimizes its own network; during online reasoning, the agent adaptively compensates the output of the MPC based on the vehicle state. The experimental results indicate that, compared with the pure MPC algorithm, the MPC algorithm compensated based on the TD3 algorithm reduces the lateral errors by 41.67% and 22.55%, respectively, in circular and double-lane-change trajectory conditions. Full article

(This article belongs to the Special Issue Recent Advances in Electrified Vehicles and Transportation Electrification)

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20 pages, 4720 KiB

Open AccessArticle

Multi-Objective Parameter Configuration Optimization of Hydrogen Fuel Cell Hybrid Power System for Locomotives

by Suyao Liu, Chunmei Xu, Yifei Zhang, Haoying Pei, Kan Dong, Ning Yang and Yingtao Ma

Electronics 2024, 13(18), 3599; https://doi.org/10.3390/electronics13183599 - 10 Sep 2024

Viewed by 1166

Abstract

Conventional methods of parameterizing fuel cell hybrid power systems (FCHPS) often rely on engineering experience, which leads to problems such as increased economic costs and excessive weight of the system. These shortcomings limit the performance of FCHPS in real-world applications. To address these [...] Read more.

Conventional methods of parameterizing fuel cell hybrid power systems (FCHPS) often rely on engineering experience, which leads to problems such as increased economic costs and excessive weight of the system. These shortcomings limit the performance of FCHPS in real-world applications. To address these issues, this paper proposes a novel method for optimizing the parameter configuration of FCHPS. First, the power and energy requirements of the vehicle are determined through traction calculations, and a real-time energy management strategy is used to ensure efficient power distribution. On this basis, a multi-objective parameter configuration optimization model is developed, which comprehensively considers economic cost and system weight, and uses a particle swarm optimization (PSO) algorithm to determine the optimal configuration of each power source. The optimization results show that the system economic cost is reduced by 8.76% and 18.05% and the weight is reduced by 11.47% and 9.13%, respectively, compared with the initial configuration. These results verify the effectiveness of the proposed optimization strategy and demonstrate its potential to improve the overall performance of the FCHPS. Full article

(This article belongs to the Special Issue Recent Advances in Electrified Vehicles and Transportation Electrification)

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17 pages, 6958 KiB

Open AccessArticle

An Improved Current Signal Extraction-Based High-Frequency Pulsating Square-Wave Voltage Injection Method for Interior Permanent-Magnet Synchronous Motor Position-Sensorless Control

by Dongyi Meng, Qiya Wu, Jia Zhang and Lijun Diao

Electronics 2024, 13(11), 2227; https://doi.org/10.3390/electronics13112227 - 6 Jun 2024

Cited by 1 | Viewed by 2359

Abstract

The high-frequency (HF) voltage injection method is widely applied in achieving position-sensorless control for interior permanent-magnet synchronous motors (IPMSMs). This method necessitates precise and rapid extraction of the current signal for accurate position estimation and field-oriented control (FOC). In the traditional methods, the [...] Read more.

The high-frequency (HF) voltage injection method is widely applied in achieving position-sensorless control for interior permanent-magnet synchronous motors (IPMSMs). This method necessitates precise and rapid extraction of the current signal for accurate position estimation and field-oriented control (FOC). In the traditional methods, the position error signal and fundamental current are extracted from the current signal using band-pass filters (BPFs) and low-pass filters (LPFs), or a method based on time-delay filters. However, the traditional extraction method falls short in ensuring simultaneous dynamic performance and accuracy, particularly when the switching frequency is limited or when encountering harmonic and noise interference. In this article, a novel HF pulsating square-wave voltage injection method based on an improved current signal-extraction strategy is proposed to improve the extraction accuracy while maintaining good dynamic performance. The newly devised current signal-extraction method is crafted upon a notch filter (NF). Through harnessing NF’s effective separation characteristics of specific frequency signals, the current signal is meticulously processed. This process yields the extraction of the position error signal and fundamental-current component, crucial for accurate position estimation and motor FOC. Simulation and hardware-in-the-loop (HIL) testing are conducted to validate the effectiveness of the proposed approach. Full article

(This article belongs to the Special Issue Recent Advances in Electrified Vehicles and Transportation Electrification)

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17 pages, 7507 KiB

Open AccessArticle

Fault Diagnosis Model for Bearings under Multiple Operating Conditions Based on Feature Parameterization Weighting

by Linghui Meng, Jinyang Xie, Zhenwei Zhou and Yiqiang Chen

Electronics 2024, 13(11), 2153; https://doi.org/10.3390/electronics13112153 - 31 May 2024

Cited by 2 | Viewed by 963

Abstract

As a core component of automobile transmission, rolling bearings play a main role in the safety and reliability of vehicles. Existing diagnostic models often treat all features equally after feature extraction, without effectively distinguishing the importance of fault features, resulting in low accuracy [...] Read more.

As a core component of automobile transmission, rolling bearings play a main role in the safety and reliability of vehicles. Existing diagnostic models often treat all features equally after feature extraction, without effectively distinguishing the importance of fault features, resulting in low accuracy and poor robustness in bearing fault diagnosis. To address this issue, a fault diagnosis model for bearings under multiple operating conditions based on feature parameterization weighting is proposed. The model utilizes a feature parameterization weighting module to categorize faults into two classes based on differences in means and implements different feature processing methods. The experimental results validate that the proposed feature parameterization weighting module effectively improves the diagnostic accuracy of the model by 8.95%. In terms of noise resistance, on two multi-condition datasets, the proposed diagnostic model achieves diagnostic accuracy of 98.79% and 98.36%. The diagnostic accuracy is improved by 15.7% and 22.48%, which indicates that the model has strong anti-noise ability. Full article

(This article belongs to the Special Issue Recent Advances in Electrified Vehicles and Transportation Electrification)

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17 pages, 5894 KiB

Open AccessArticle

Nonlinear Modeling and Control Strategy Based on Type-II T-S Fuzzy in Bi-Directional DC-AC Converter

by Zhihua Chen, Ruochen Huang, Qiongbin Lin, Xinhong Yu and Zhimin Dan

Electronics 2024, 13(9), 1684; https://doi.org/10.3390/electronics13091684 - 26 Apr 2024

Cited by 2 | Viewed by 1367

Abstract

Bi-directional DC-AC converters are widely used in the field of electric vehicle-to-grid. However, the inductance of the grid-side interface filter is affected by the length of the grid connection and the power level, which presents nonlinear characteristics. This poses challenges for high-performance grid [...] Read more.

Bi-directional DC-AC converters are widely used in the field of electric vehicle-to-grid. However, the inductance of the grid-side interface filter is affected by the length of the grid connection and the power level, which presents nonlinear characteristics. This poses challenges for high-performance grid waveform control. In this paper, a modeling method for bi-directional DC-AC grid-connected converters based on type-II T-S fuzzy models is proposed, and the corresponding type-II T-S fuzzy control strategy is designed to address the parameter uncertainty and non-linearity issues. Simulation results show that type-II T-S fuzzy control offers superior control performance and better current waveform quality compared to type-I T-S fuzzy control under uncertainty parameter conditions. The effectiveness of the proposed strategy is further validated through a 1 kW prototype of a bi-directional DC-AC converter. Full article

(This article belongs to the Special Issue Recent Advances in Electrified Vehicles and Transportation Electrification)

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15 pages, 9551 KiB

Open AccessArticle

Analysis of Pressure Characteristics of Ultra-High Specific Energy Lithium Metal Battery for Flying Electric Vehicles

by Wei Shi, Jin Chai and Ruofan Xu

Electronics 2024, 13(8), 1505; https://doi.org/10.3390/electronics13081505 - 16 Apr 2024

Cited by 1 | Viewed by 1296

Abstract

The lithium metal battery is likely to become the main power source for the future development of flying electric vehicles for its ultra-high theoretical specific capacity. In an attempt to study macroscopic battery performance and microscopic lithium deposition under different pressure conditions, we [...] Read more.

The lithium metal battery is likely to become the main power source for the future development of flying electric vehicles for its ultra-high theoretical specific capacity. In an attempt to study macroscopic battery performance and microscopic lithium deposition under different pressure conditions, we first conduct a pressure cycling test proving that amplifying the initial preload can delay the battery failure stage, and the scanning electron microscope (SEM) shows that the pressure is effective in improving the electrode’s surface structure. Secondly, we analyze how differing pressure conditions affect the topography of lithium deposits by coupling the nonlinear phase-field model with the force model. The results show that the gradual increase in the external pressure is accompanied by a drop in the length of the dendrite and the migration curvature in the diaphragm, and the deposition morphology is gradually geared towards smooth and thick development, which can significantly reduce the specific surface area of lithium dendrite. However, as cyclic charging and discharging continue, the decrease in the electrolyte diffusion coefficient results in higher internal stress inside the battery, and thus the external pressure must be increased so as to achieve marked inhibitory effects on the growth of the lithium dendrite. Full article

(This article belongs to the Special Issue Recent Advances in Electrified Vehicles and Transportation Electrification)

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