Volume 47,Issue 3,2024 Table of Contents

1 Path following control of intelligent vehicles based on multi-model adaptive method

LIANG Yixiao , LI Yinong , Amir Khajepour , ZHENG Ling , YU Yinghong , ZHANG Ziwei

2024, 47(3):1-15. DOI: 10.11835/j.issn.1000-582X.2022.109

[Abstract](335) [HTML](60) [PDF 4.43 M](569)

Abstract:
Path following control is a crucial technology for intelligent vehicles, and the control accuracy and the robustness under various road adhesive conditions are two key elements of this technology. However, the accuracy and the robustness are hard to be achieved simultaneously owing to the uncertainties in a vehicle dynamics model, especially the perturbation of tire cornering stiffness. To deal with the uncertainties, a multi-model adaptive method is introduced in this study. Firstly, the basic theory of the method is derived, and the adaptive law of each vertex sub-model to the real model is proposed, with its convergence proved by the Lyapunov theory. Then, a vehicle dynamics model and a vehicle-road combined model are built, and the convex polyhedron including all possible perturbation of tire cornering stiffness is established with multiple sub-models. The adaptive law is derived according to the vehicle dynamics model, and the feedback controller of the sub-model in each vertex is derived by the linear quadratic regulator (LQR) method based on the vehicle-road combined model. Simulation results show that the proposed controller can not only ensure the robustness, but also overcome the conservative problem of previous robust methods, achieving excellent performance under various road conditions. Finally, a rapid prototyping test platform is established for further evaluation. Results show that the proposed algorithm has excellent real-time performance, suggesting an excellent potential of its engineering application.

2 Lane-changing decision and planning with established safe lane-changing domain

WANG Haisong , HU Minghui , LI Wanhong , CAO Kaibin

2024, 47(3):16-29. DOI: 10.11835/j.issn.1000-582X.2022.117

[Abstract](285) [HTML](53) [PDF 3.39 M](501)

Abstract:
Local path planning emphasizes generating a drivable path in micro traffic scenarios, which requires high safety and comfort for each discrete point along the path. At present, few local path planning methods consider physical characteristics such as continuity of path curvature and constraints on the starting and ending points of the path. In this study, a lane-changing decision and planning method based on a safe lane-changing domain is explored. A critical safe lane-changing angle model is established for typical lane-changing scenarios, and for lane-changing scenarios involving dual obstacles that cannot evolve into single-obstacle lane-changing scenarios, a safe lane-changing domain is established. Several commonly used lane-changing paths are compared, and the B-spline curve method is selected as the local path planning method. The optimal lane-changing path based on the safe lane-changing domain is determined using the lane-changing time and the average curvature of the lane-changing path. A lane-changing decision strategy based on the safe lane-changing domain is proposed. Simulation verification of the proposed lane-changing strategy is realized in typical lane-changing scenarios by using the Simulink and PreScan computing platforms. The results show that the proposed lane-changing decision and lane-changing path planning can achieve a safe lane change for the ego vehicle.

3 Decision making and optimization of trajectory planning of lane change on highway curve

YUAN Chang , MO Tianshi , SHU Hong

2024, 47(3):30-43. DOI: 10.11835/j.issn.1000-582X.2023.221

[Abstract](250) [HTML](39) [PDF 2.97 M](643)

Abstract:
Decision making and motion planning algorithms play a crucial role in determining the safety and handling stability of autonomous vehicles, particularly on highway curves. Addressing safety and driving efficiency concerns in the decision-making process for highway lane changes, this study proposes a driving dissatisfaction decision algorithm based on the relative driving dissatisfaction of the ego-vehicle compared to the preceding vehicle. To improve the real-time performance of the planning algorithm, a path-speed decoupling framework is adopted for lane change trajectory planning. The path planning utilizes the quintic polynomial curve, incorporating four path evaluation indicators that considered safety, comfort and efficiency to achieve optimal path planning. Speed planning involves obtaining a smooth speed curve through a combination of dynamic programming and quadratic programming optimization. Simulation results show that the lane change decision model based on driving dissatisfaction can choose a more efficient and safer driving mode. In typical lane changing scenarios, both the maximum centroid sideslip angle and maximum yaw rate of the ego-vehicle are small, indicating that the lane change trajectory planning algorithm can ensure the safety and handling stability of the ego-vehicle during the lane change process.

4 Vehicle speed estimation based on a modified particle filter algorithm

GAO Yan , FU Chunyun , YANG Zhong , YANG Guanlong

2024, 47(3):44-52. DOI: 10.11835/j.issn.1000-582X.2022.111

[Abstract](294) [HTML](60) [PDF 1.22 M](440)

Abstract:
For conventional vehicle speed estimators designed based on the particle-filter algorithm, the estimation performance deteriorates if the proposal distribution is inconsistent with the actual distribution. In this paper, an improved particle-filter speed estimator is proposed to tackle this problem by modifying the proposal distribution. Firstly, the state transition equation and the observation equation of the system are established based on vehicle kinematics and sensor characteristics. Then, the difference between sensor measurements and particle state values is employed to design a correction term for the proposal distribution, simultaneously adapting the process noise in the state transition equation. Finally, simulation validation is conducted using CarSim-Simulink co-simulation platform under the double-lane change and the sine-wave steer input maneuvers. Compared with the adaptive particle filter, the proposed estimator shows reductions of 40.25% and 55.71% in the mean absolute deviations (MAD) of the estimated longitudinal velocity and the estimated lateral velocity, respectively, under the double-lane change maneuver; and under the sine-wave steer input maneuver, the reductions are 47.00% and 41.21%, respectively.

5 Analysis and prediction of motor vehicle speed characteristics under the influence of roadside intrusions

XIE Jiming , QIAN Zhengfu , XIA Yulan , ZHAO Pengyan , QIN Yaqin

2024, 47(3):53-65. DOI: 10.11835/j.issn.1000-582X.2022.127

[Abstract](246) [HTML](48) [PDF 6.60 M](532)

Abstract:
Low-grade roads often experience frequent roadside intrusions, leading to serious conflicts and disorder. Accurate prediction of the complex traffic-behavior characteristics on such roads is essential for understanding the mechanisms of traffic accidents influenced by roadside intrusions. For this purpose, we collected videos depicting five types of common roadside intrusions on low-grade highways and urban roads. From these videos, we extracted high-resolution vehicle micro-trajectories, and determined the vehicle speeds as they traversed the intrusion area. Then, we identified characteristic sections within the intrusion area, and analyzed the evolution of spatial and temporal characteristics of the vehicle speed. Finally, we established a vehicle speed prediction model using linear, logarithmic and cubic regressions. Notably, the cubic regression model exhibited superior speed prediction performance in the complex scenarios of the intrusion area. The results showed that speed reduction in the intrusion zone of low-grade urban roads is typically higher than that on highways. The deceleration effect is significant for drivers approaching the intrusion source. Additionally, drivers tend to accelerate through the front intrusion zone when their intentions align with those of the intrusion source. However, in scenarios where predicting the behavioral intentions of the intrusion source is challenging, speed may fluctuate to some extent.

6 Aluminum stress distribution of long-span transmission line

WANG Feng , ZENG Chao , XUE Chunlin , WEN Zuoming

2024, 47(3):66-74. DOI: 10.11835/j.issn.1000-582X.2021.225

[Abstract](166) [HTML](35) [PDF 2.81 M](381)

Abstract:
To analyze the spatial distribution of aluminum stress in long-span overhead transmission line, this study focused on the JLHA1/G6A-500/280 ultra strong steel cored aluminum alloy conductor. A stress test platform for aluminum in long-span conductors was established using laser grooving on the aluminum strand and embedding ultra weak fiber gratings known for their high sensitivity and super multiplexing capacity. The research investigated the aluminum stress distribution in the long-span overhead transmission conductor under various tension conditions. A finite element model of the long-span conductor was created, and the stress distribution characteristics of the aluminum strand was analyzed, with the test results validated against the model. The results show that under tension, the stress in the outer aluminum strand differs from that in the sub outer aluminum strand, with the outer aluminum strand experiencing lower stress. The stress within the same layer of the conductor remains consistent. The aluminum strand stress increases linearly with the increase of conductor tension, with a roughly 10% increase in aluminum strand stress for every 1% increase in tension. Under different conductor tensions, both steel and aluminum strands show ring delamination characteristics. The average stress in the aluminum strand is less than that in the steel strand, with a stress ratio of approximately 3∶7 between aluminum and steel strands. Additionally, the stress distribution of the aluminum alloy strand in the outer layer and sub outer layer is uneven along the circumferential direction. This study suggests considering the delamination characteristics of the aluminum strand in the linear design of long-span conductors.

7 Design of handheld intelligent magnetic susceptibility meter based on resonance method

JIN Zhengwei , FU Zhihong , ZHANG Jin

2024, 47(3):75-85. DOI: 10.11835/j.issn.1000-582X.2022.206

[Abstract](114) [HTML](45) [PDF 3.06 M](385)

Abstract:
In this paper, a handheld intelligent susceptibility meter was designed based on the resonance principle. A calculation formula for the resonance principle method was derived to measure the magnetic susceptibility of rock. Simulation of the influencing factors of the resonance method was conducted to explore the magnetic susceptibility of rock. The overall design of the instrument was informed by the simulation results and actual detection needs. The peripheral circuit was constructed based on LDC1614, and the inductance sensor, signal extraction program, and operation interface for the upper computer were designed. The prototype of the magnetic susceptibility instrument was completed. The instrument is portable (weighing only 0.2 kg) and is easy to operate. The measurement error is less than 5% compared with similar foreign instruments, and the accuracy of the instrument can reach 10^-7. It is suitable for both field and laboratory measurements and holds practical engineering value.

8 Discriminative transfer feature for motor imagery brain-computer interfaces

QI Lei , CHEN Minyou , ZHANG Li

2024, 47(3):86-95. DOI: 10.11835/j.issn.1000-582X.2022.207

[Abstract](127) [HTML](50) [PDF 2.53 M](406)

Abstract:
To address the cross-sessions variability of motor imagery electroencephalogram (EEG) and eliminate the need for lengthy recalibration step, this study proposes a motor imagery classification method based on discriminative transfer feature learning (DTFL). DTFL aims to reduce domain differences by jointly matching the marginal distribution and class conditional distribution of both domains. Simultaneously, DTFL maximizes inter-class dispersion and minimizes intra-class scatter, preserving class discrimination information and improving classification performance. This method does not require class information for EEG samples in the target domain, effectively avoiding the need for long-term calibration. Experimental results on brain-computer interface competition datasets demonstrate that, compared with some transfer learning methods, the proposed DTFL mitigates cross-session variability and improves the classification accuracy of motor imagery EEG.

9 Bearing fault feature extraction method based on enhanced combination difference multiply morphological filter

XU Xianfeng , ZHAO Weifeng , ZOU Haoquan , SONG Yanan

2024, 47(3):96-106. DOI: 10.11835/j.issn.1000-582X.2022.011

[Abstract](118) [HTML](48) [PDF 3.32 M](383)

Abstract:
To address the limitations of conventional time-frequency domain feature extraction methods when dealing with the non-linear, non-stationary and strongly noisy characteristics of rolling bearing fault signals, a bearing fault feature extraction method based on an enhanced combination difference multiply morphological filter is proposed in this study. Based on the understanding of the positive and negative shock pulse extraction characteristics of the four basic operations of mathematical morphology, a new combination difference multiply operator (CDMO) is constructed. This CDMO has the ability to simultaneously extract positive and negative shock pulses by combining cascade, difference and multiply operations. The gradient multiply operation that is more sensitive to pulse extraction is utilized to achieve comprehensive fault information extraction. The fault characteristic frequency ratio index is introduced to optimize the parameters of the CDMO structural elements. This optimization modifies the geometric characteristics of the signal to be processed, allowing for the extraction of signal characteristic information that matches the structural elements. Following CDMO filtering, third-order cumulant slice spectrum technology is employed to suppress Gaussian noise and highlight the advantages of secondary coupling components. This enhances the ability to accurately extract fault feature frequencies and their multiplications, thus improving bearing fault feature extraction and suppressing noise interference. The proposed method’s effectiveness is verified by relying on actual engineering signals from two different sources and comparing its performance with classic fault feature extraction methods.

10 Control-oriented one-dimensional model for non-isothermal two-phase transport in fuel cells

LIU Jiaqi , LU Chihua , LIU Zhien , ZHOU Hui

2024, 47(3):107-119. DOI: 10.11835/j.issn.1000-582X.2022.005

[Abstract](142) [HTML](39) [PDF 3.23 M](453)

Abstract:
The empirical model fails to capture the complex physical and chemical coupling processes occurring within the battery and the resulting response hysteresis, posing challenges for the development of precise control strategies for fuel cell systems. To address this issue, a control-oriented one-dimensional non-isothermal two-phase flow model was developed, with the transient effects of gas in the flow channel and the phase transition of water in the battery taken into account. The effects of current density on gas concentration and water-heat distribution characteristics were investigated. The impacts of operating conditions and model parameters on the output voltage of the battery were studied, and the advantages of the proposed model compared to the lumped parameter model in terms of output performance under current steps were analyzed. The results show that the model exhibits better applicability, providing a reliable foundation for model optimization and the design of control strategies at the fuel cell system level.

11 Dynamic characteristics of a gearbox-generator integrated system with housing flexibility

CHEN Ruibo , QIN Datong , LIU Changzhao

2024, 47(3):120-131. DOI: 10.11835/j.issn.1000-582X.2022.121

[Abstract](109) [HTML](48) [PDF 4.77 M](407)

Abstract:
For the integrated structure of the wind power transmission system, an electromechanical rigid-flexible coupling dynamics model suitable for wind turbine generator under variable-speed and variable-load conditions was proposed. This model considered mechanical factors such as time-varying meshing stiffness of gears, phase relationship, and structural flexibility of the shaft and shell, as well as electromagnetic factors such as saturation characteristics of permanent magnet, radial force wave and space harmonic wave. The electromechanical coupling dynamic characteristics of the gearbox-generator integrated system were investigated, and the influence of the flexibility of the housing on the dynamic characteristics of the system was discussed. An acceleration analysis method was introduced to identify the resonance speed of the system. By using the modal energy method and the formation vector distribution principle, potential dangerous components in resonance were identified. The results show strong coupling between the gear system and the generator. The flexibility of the housing has a significant effect on the electromechanical coupling characteristics of the system. For the integrated system, internal gear excitation is the main excitation source at the resonant speed. However, when a thin-wall housing is used, electromagnetic excitation from the generator cannot be ignored, making it easy to stimulate new resonance speeds. Selecting a reasonable thickness can effectively improve the safety and reliability of the system, reduce the resonance area and mitigate damage to system components.

12 Effects of environmental parameters on fatigue damage of wind turbine gearbox transmission system

WU Yuan , ZHU Caichao , TAN Jianjun , SONG Chaosheng , ZHANG Huiyang

2024, 47(3):132-144. DOI: 10.11835/j.issn.1000-582X.2022.115

[Abstract](146) [HTML](52) [PDF 4.09 M](470)

Abstract:
In the entire life cycle of a wind turbine, the probability distribution of long-term wind speeds introduces randomness to the dynamic load on the wind turbine gearbox transmission system appear random, thereby affecting the accuracy of fatigue damage prediction. In this paper, a fatigue damage prediction method is proposed for the wind turbine gearbox transmission system with considering the characteristics of the long-term wind speed probability distribution. The approach involves assessing the short-term fatigue damage of gears in the transmission system of wind turbine gearbox based on an OpenFAST-SIMPACK combined simulation model built for high power offshore wind turbines. Subsequently, surrogate model technology is used to reconstruct the mapping relationship between “average wind speed, turbulence intensity, and short-term fatigue damage” enabling the prediction of long-term fatigue damage for the gears. The research results show that the low-speed sun gear in the wind turbine gearbox transmission system is prone to contact fatigue failure. Below the rated wind speed, the short-term fatigue damage of the low-speed sun gear correlates positively with the average wind speed, thereby increasing the uncertainty of long-term fatigue damage and elevating the risk of fatigue failure.

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