Volume 44,Issue 12,2021 Table of Contents

1 Analysis and comparison of the flexible and load sharing and dynamic load factor of the type of ring gear

HU Shengyang , FANG Zongde , XU Yingqiang , SHEN Rui

2021, 44(12):1-14. DOI: 10.11835/j.issn.1000-582X.2020.026

[Abstract](380) [HTML](507) [PDF 2.51 M](812)

Abstract:
With the development of industry, higher requirements for the load sharing and dynamic load factor of planetary transmission system have been put forward. On the basis of traditional ring gear structure, thin-walled ring gear, new material ring gear and elastic support ring gear have been designed and applied. However, the structural characteristics and flexibility differences of each ring and their influence on the system load sharing and dynamic load factor have been rarely reported in the literature, resulting in the blind spot in the design and selection of the system components. In this paper, by establishing the finite element models of each ring structure, the structural characteristics and flexibility differences of each ring were compared and analyzed. Combined with the dynamic model of planetary transmission system, the differences of the system's load sharing and dynamic load factor under different structures were obtained when the system errors were considered. The analysis shows that the flexibility of the traditional ring gear is the worst, and the system's load sharing and dynamic load factor are obviously larger than those of the flexible ring gear. The thin-walled flexible ring gear has the best load-sharing effect and the fluctuation is smooth, but the dynamic load factor fluctuation of each branch of the system increases. Due to the structural characteristics of the elastic-pin ring gear, the comprehensive time-varying meshing stiffness fluctuates violently, and the stiffness increases obviously when it is at the pin position. Although the load sharing of the system is reduced, it is chaotic and the dynamic load factor of the system is obviously enhanced.

2 Lane-changing trajectory tracking method by integrated modified feasibility test model

XIANG Yunfeng , HE Yansong , KONG Weiwei , CHEN Jian , LUO Yugong

2021, 44(12):15-30. DOI: 10.11835/j.issn.1000-582X.2020.030

[Abstract](429) [HTML](436) [PDF 913.01 K](603)

Abstract:
The existing minimum safe distance lane changing feasibility test models usually consider the surrounding vehicles in the lane-keeping and only discuss the influence of the vehicles in present lane and the target lane. The influences of the surrounding vehicles in the lane-changing or in the interphase lane are not considered. To ensure that the vehicle would not collide with the surrounding vehicles during the lane-changing, a modified lane changing feasibility test model which considered the surrounding vehicles (in the adjacent lanes and in the interphase lanes) in the lane-changing or lane-keeping state was proposed. Firstly, the logic framework of lane-changing was analyzed. The trajectory tracking control was then completed based on the model predictive control (MPC) method. Finally, a simulation comparison test was designed and the proposed model and method were verified by the PreScan and Simulink co-simulation. The simulation results show that the proposed improved lane-changing feasibility test model is safer and more efficient than the existing model. The tracking error of the MPC controller is within 1 cm, suggesting that the proposed model has high tracking accuracy.

3 Global optimal path planning considering time-varying weight of road network

LI Wanhong , HU Minghui , CHEN Long , RAO Kun

2021, 44(12):31-42. DOI: 10.11835/j.issn.1000-582X.2020.032

[Abstract](436) [HTML](952) [PDF 2.61 M](785)

Abstract:
Because static path planning (SPP) and rolling path planning (RPP) cannot solve the global optimal path, a global optimal path planning method (GOPP) considering the time-varying characteristics of road network weights was proposed. Vissim software was used to model and simulate a regional road network in Chongqing University Town, and the improved forward associated edge data structure was used to store the road network topology key elements and travel time simulation data, which were used as the path planning database. On this basis, the actual weights of cross period road sections were derived, and a GOPP method based on Dijkstra algorithm was proposed. Based on the path planning database, the classical Dijkstra algorithm was proved to have the global optimal solution ability compared with the intelligent heuristic algorithm. Finally, three planning paths in Matlab software were simulated by using the SPP, RPP and GOPP methods. The results show that the cumulative travel time of GOPP is 1 158.7 s, which is 212.7 s and 57.6 s less than those of SPP and RPP, respectively, verifying that GOPP is superior in shortening travel time. The proposed GOPP has certain theoretical significance for the development of intelligent vehicles in the future.

4 Impact of cumulative positive elevation gain on real driving emission test of light-duty gasoline vehicle

ZOU Jie , DU Baocheng , YUE Dajun , CHEN Lingjian , XU Hualong , ZHANG Li

2021, 44(12):43-53. DOI: 10.11835/j.issn.1000-582X.2020.021

[Abstract](462) [HTML](828) [PDF 5.55 M](702)

Abstract:
In Southwest China, the road surface fluctuates greatly, which has a great influence on the real driving emissions. In this paper, RDE (real driving emission) tests on four routes of different cumulative positive elevation gains were conducted by using a light-duty gasoline vehicle that meets China-6 emission regulation standards. The correlation between cumulative positive elevation gainor dynamic parameter v·a_pos[95] of road section and window and pollutant emission factors (CO, CO₂, NO_x and PN) was analyzed.The results show that the correlation between pollutant emissions and cumulative positive elevation gain or v·a_pos[95] was not strong in the road section. In the window, when v·a_pos[95] was large, there was a significant correlation between CO emission and cumulative positive elevation gain. CO₂ emission increased with the increase of cumulative positive elevation gain, and was less affected by v·a_pos[95]. No significant correlation was found between NO_x emission and cumulative positive elevationgain or v·a_pos[95]. In the range of high v·a_pos[95], PN emission had a significant correlation with cumulative positive elevation gain,while in the range of low v·a_pos[95], PN emission had no significant correlation with cumulative positive elevation gain. The suggestion is to set different limits on the cumulative positive elevation gain of urban, rural and motorway sections.

5 Optimization method of vehicle body structure in conceptual design stage of platform architecture

ZHANG Feng , DUAN Wenli , LIU Yangsheng , SHI Danghe , CHEN Yuqi

2021, 44(12):54-70. DOI: 10.11835/j.issn.1000-582X.2020.029

[Abstract](401) [HTML](572) [PDF 9.73 M](924)

Abstract:
To optimize vehicle body structure in the conceptual design stage of platform architecture, a new method was proposed. The method includes three stages. In the first stage, considering the real collision load, the multi-model optimization method was used to carry out the global topology optimization under the comprehensive working condition, and the different force transmission paths were interpreted. In the second stage, considering the high and low vehicles of the platform architecture, the body parameter models of different transmission paths were established using SFE CONCEPT. Comparative analysis and optimization were conducted under different power types to determine the form of transmission path of the platform architecture. In the third stage, the approximate model method was adopted to optimize the body section and the equivalent static load method was adopted to optimize the body material thickness, and the optimization scheme was put into different vehicle and power types for verification and optimization, so as to ensure that the body structure was under the target performance bandwidth of platform architecture. In the conceptual design stage of the platform architecture of an automobile enterprise, the proposed method was used to optimize the body structure, and the engineering feasibility of this method was verified.

6 Vehicle information detection based on improved YOLOv3 algorithm

FENG Jiaming , CHU Maoxiang , YANG Yonghui , GONG Rongfen

2021, 44(12):71-79. DOI: 10.11835/j.issn.1000-582X.2020.016

[Abstract](562) [HTML](665) [PDF 2.95 M](782)

Abstract:
Vehicle information detection is the primary task of vehicle type identification in the field of intelligent transportation. Based on deep learning YOLOv3 (You Only Look Once Version 3) model, a new YOLOv3-fass object detection algorithm was proposed to address some problems existing in vehicle information detection technology such as detection speed, accuracy and stability. In this improved algorithm, based on DarkNet-53 network structure, some residual structures were deleted, and a number of channels of convolutional layer were reduced; a down-sampling branch, three scale-hopping connection structures, and one detection scale were added; and twelve groups of anchor frame values were calculated through the means of K-means clustering algorithm combined with manual setting. Finally, YOLOv3-fass algorithm was fine-tuned through the migration learning mechanism of multi-stage pre-training. YOLOv3-fass algorithm was compared with YOLOv3, YOLOv3-tiny, YOLOv3-spp and two algorithms with ResNet50 and DenseNet201 on the vehicle data set. The experimental results show that YOLOv3-fass algorithm can detect vehicle information more accurately, efficiently and stably.

7 Adaptive equivalent consumption minimization strategy for plug-in hybrid electric vehicle

HU Jianjun , YANG Ying , ZOU Lingbo , PENG Tao

2021, 44(12):80-94. DOI: 10.11835/j.issn.1000-582X.2020.031

[Abstract](616) [HTML](2682) [PDF 4.30 M](947)

Abstract:
In order to improve the fuel economy of plug-in hybrid vehicles (PHEV), the optimal trajectories of state of charge (SOC) under different typical driving cycles and different driving distances were simulated and analyzed by using dynamic programming (DP) algorithm. On the basis of equivalent fuel consumption minimum strategy (ECMS), PI control was used to update the energy fuel equivalent factor in real time, so as to ensure that the actual SOC trajectory could roughly follow the theoretical reference trajectory, and then an adaptive equivalent consumption minimization strategy (AECMS) which can be controlled in real time was proposed. To verify the effectiveness of the proposed control strategy, different typical working conditions and driving mileages were used to simulate and compare the control performances of ECMS, DP and AECMS. The results show that the control effect of AECMS was close to that of DP and could be controlled in real time. AECMS reduced fuel consumption by 3.50%~8.71% in CD mode and 1.11%~2.46% in CS mode compared with ECMS.

8 Improved YOLOv3 algorithm for vehicle detection in hazy weather

HUANG Kaiqi , LIU Xiaorong , QIAN Yanqun , HUANG Maoyun

2021, 44(12):95-102. DOI: 10.11835/j.issn.1000-582X.2020.027

[Abstract](392) [HTML](653) [PDF 9.65 M](672)

Abstract:
Traditional YOLOv3 algorithm has the problem of inaccurate detection frame positioning. In this paper, an improved YOLOv3 algorithm was proposed to re-estimate the detection frame position and improve the positioning accuracy of smart cars in hazy traffic environment. Firstly, the collected images were preprocessed using image dehazing algorithms. Then, to improve positioning accuracy, estimated test box position was selected by constructing positioning confidence as the reference to replace classification confidence, and the non-maximum suppression (NMS) algorithm was improved. Finally, the soft-NMS was introduced, and the coordinates were updated using the weighted average. The experimental results show that compared with the original YOLOv3 algorithm, the mAP(mean average precision) of improved YOLOv3 algorithm increased by 0.44%, which could detect more targets and locate the detected vehicles more accurately in real-time detection.

9 Effect of driving style on the energy consumption of an electric vehicle

ZHAO Jiawei , HU Minghui , RONG Zhengbi , FU Chunyun

2021, 44(12):103-115. DOI: 10.11835/j.issn.1000-582X.2020.025

[Abstract](409) [HTML](700) [PDF 5.64 M](720)

Abstract:
The energy consumption of electric vehicle (EV) is affected by many factors. In order to reveal the influence of driving style on the energy consumption of EV, the energy consumption experiment of the whole vehicle was designed by controlling the univariate factor. Through the combination of experimental test and theoretical calculation, the energy distribution of each component was obtained, and the energy consumption was quantitatively analyzed to highlight the direction for optimizing the energy consumption of EV. Firstly, the energy flow of EV under the condition of constant speed was analyzed, identifying the influence of certain factors on the vehicle energy consumption. Then the influence of driving style on the energy consumption of EV was analyzed under the comprehensive working conditions. The results show that the battery energy was mainly consumed by the electric motor control system and vehicle driving resistance, and the energy consumption of accessories was very little. The driving style mainly causes the fluctuation of energy consumption by affecting the braking loss and the operating efficiency of power transmission system. Different driving styles will lead to a difference of more than 10 kW·h in the energy consumption per 100 km.

10 An improved differential evolution algorithm for simultaneous scheduling of machines and AGVs in an FMS

WU Yue , SONG Yuchuan , LYU Xiangfei , LEI Qi

2021, 44(12):116-129. DOI: 10.11835/j.issn.1000-582X.2020.024

[Abstract](326) [HTML](548) [PDF 2.62 M](814)

Abstract:
An improved discrete differential evolution algorithm with variable neighborhood search was proposed for solving simultaneous scheduling of machines and AGVs in flexible manufacturing systems. With the optimization goal of making the maximum completion time minimum, considering the dual resource constraints of machines and AGVs, the corresponding mathematical model was established. The three-layer coding structure of operation,machine and AGV was employed to schedule machines and AGVs simultaneously. In order to improve the global search capability, the differential evolution algorithm generated new individuals by improved mutation and crossover operators, and introduced the acceptance criterion of solution in simulated annealing algorithm to select next generation. Furthermore, a variable neighborhood search was performed on the optimal individual in each iteration of the algorithm in order to enhance the local search capability. Finally, the effectiveness, stability and superiority of the improved differential evolution algorithm were proved by calculation and comparison of examples.

11 Design and application of online fault diagnosis system for gear box

ZHANG Haonan , ZHANG Youkun , WANG Lin , SHI Tongjie

2021, 44(12):130-139. DOI: 10.11835/j.issn.1000-582X.2020.020

[Abstract](418) [HTML](817) [PDF 8.29 M](859)

Abstract:
In order to detect the occurrence and location of the faults in the life test of the gearbox bench as soon as possible and to avoid causing damage to the test equipment and personnel, a gearbox online fault diagnosis system is developed. The system uses acceleration sensors to detect the vibration signals of the box and realizes real-time monitoring and fault early warning of the gearbox test through time-frequency domain analysis. The system performs time-frequency domain analysis on time-domain signals by using ZFFT refined spectrum method to process frequency-domain signals, and analyzing the characteristics of typical fault signals to realize fault type determination. The test results show that the system can realize gearbox failure prediction and accurately identify typical failures.

12 Path planning of mobile robots based on improved algorithm

XIE Chongchong , LI Ying

2021, 44(12):140-148. DOI: 10.11835/j.issn.1000-582X.2021.12.012

[Abstract](452) [HTML](1000) [PDF 5.26 M](553)

Abstract:
In order to make full use of the advantages of genetic algorithm and the whale method in the algorithm, the improved genetic algorithm is integrated with the whale method to enhance the adaptability of the mobile robot path planning to the dynamic environment. By optimizing the fitness function of the algorithm, the basic genetic algorithm is improved so that the solving speed of the original algorithm is improved. Compared the path length and running time of the three algorithms:genetic algorithm, improved genetic algorithm and improved genetic whale algorithm, the results show that the improved genetic whale algorithm can continuously extract the optimal operator, reduce the number of iterations, and improve the accuracy of path planning.

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