International Journal of Automotive Technology最新文献_第3页

Localization and Mapping Based on Multi-feature and Multi-sensor Fusion 基于多特征和多传感器融合的定位与测绘

IF 1.6 4区工程技术

International Journal of Automotive Technology Pub Date : 2024-07-24 DOI: 10.1007/s12239-024-00122-7

Danni Li, Yibing Zhao, Weiqi Wang, Lie Guo

{"title":"Localization and Mapping Based on Multi-feature and Multi-sensor Fusion","authors":"Danni Li, Yibing Zhao, Weiqi Wang, Lie Guo","doi":"10.1007/s12239-024-00122-7","DOIUrl":"https://doi.org/10.1007/s12239-024-00122-7","url":null,"abstract":"Simultaneous Localization and Mapping (SLAM) is the foundation for high-precision localization, environmental awareness, and autonomous decision-making of autonomous vehicles. It has developed rapidly, but there are still challenges such as sensor errors, data fusion, and real-time computing. This paper proposes an optimization-based fusion algorithm that integrates IMU data, visual data and LiDAR data to construct a high-frequency visual-inertial odometry. The odometry is employed to obtain the relative pose transformation during the LiDAR data acquisition process, and eliminate the distortion of the point cloud by interpolation. By utilizing the local curvatures, some edge and plane features are extracted by LiDAR after removing the distortion, which are further combined with local map alignment to reconstruct the LiDAR constrains. In addition, the LiDAR odometer can be obtained through the initial values provided by high-frequency visual-inertial odometry. To address the cumulative error in odometers, adjacent keyframe and multi descriptor fusion loop constraints are combined to construct back-end optimization constraints, solving for high-accuracy localization results and constructing a 3D point cloud map of the surroundings. Compared with some classical algorithm, results show that the accuracy of this paper's algorithm is better than the laser SLAM method and the multi-sensor fusion SLAM method. Besides, the laser-assisted multi-feature visual-inertial odometry localization accuracy is also better than that of the single-feature visual-inertial odometry. In summary, the newly proposed SLAM method can largely improve the accuracy of odometry in real traffic scenarios.","PeriodicalId":50338,"journal":{"name":"International Journal of Automotive Technology","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141786149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on Variable Displacement Valve Control Strategy Based on Electro-hydraulic Drive Intake and Exhaust Valve Opening and Closing Mode 基于电液驱动进排气门开闭模式的变排量气门控制策略研究

IF 1.6 4区工程技术

International Journal of Automotive Technology Pub Date : 2024-07-24 DOI: 10.1007/s12239-024-00124-5

Zhaohui Jin, Dayou Lu, Tian You, Fangxi Xie

引用次数: 0

NOX Emission Prediction of Diesel Engine Based on GWO-LSTM 基于 GWO-LSTM 的柴油发动机氮氧化物排放预测

IF 1.6 4区工程技术

International Journal of Automotive Technology Pub Date : 2024-07-09 DOI: 10.1007/s12239-024-00068-w

Biwei Lu, Jiehui Li

{"title":"NOX Emission Prediction of Diesel Engine Based on GWO-LSTM","authors":"Biwei Lu, Jiehui Li","doi":"10.1007/s12239-024-00068-w","DOIUrl":"https://doi.org/10.1007/s12239-024-00068-w","url":null,"abstract":"Diesel engine NOx is the main harmful emission of motor vehicles. Accurate measurement of NOx emission is beneficial to the control of SCR (selective catalytic reduction) urea injection so as to reduce emissions. At present, NOx emission value is mainly obtained by NOx sensor or MAP calibration and these two methods have limitations in practical applications. In this study, PCA (principal component analysis) is used to reduce the dimension of diesel engine operating data of WHTC (the world harmonized transient cycle) bench test, which can make data visualized in three-dimensional space. Then transient diesel engine NOx prediction model is built based on LSTM, and GWO (grey wolf optimizer) is used to optimize the parameters of LSTM. The results showed that R2 (determination coefficients) of the GWO-LSTM is 0.987; In the untrained data set, MAE (mean absolute error), MAPE (mean absolute percentage error) and RMSE (root mean square error) are 18.75 × 10–6, 3.23% and 20.29 × 10–6, respectively. The same accuracy index are be compared with PSO-BP and static map. It is proved that the GWO-LSTM model can accurately predict the transient NOx emission of diesel engine, and also has good generalization ability with reliability, which provides a reference for software instead of hardware to control diesel engine emission.","PeriodicalId":50338,"journal":{"name":"International Journal of Automotive Technology","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141568068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Study on the Necessity of Real-World Driving Tests for Passenger Electric Vehicles 关于乘用电动汽车实际驾驶测试必要性的研究

IF 1.6 4区工程技术

International Journal of Automotive Technology Pub Date : 2024-07-05 DOI: 10.1007/s12239-024-00108-5

Gwangryeol Lee, Jeonghyun Park, Suhan Park, Seung Hyun Yoon

引用次数: 0

Erratum: Effects of Various Compression Ratios on a Direct Injection Spark Ignition Hydrogen-Fueled Engine in a Single-Cylinder Engine 更正：各种压缩比对单缸直喷式火花点火氢燃料发动机的影响

IF 1.5 4区工程技术

International Journal of Automotive Technology Pub Date : 2024-07-02 DOI: 10.1007/s12239-024-00120-9

Seungjae Kim, Jeongwoo Lee, Seungil Lee, Seunghyun Lee, Kiyeon Kim, Kyoungdoug Min

引用次数: 0

Calculation and Correction Method of Dynamic Tire Loads in Accelerating and Braking Conditions 加速和制动条件下轮胎动载荷的计算和修正方法

IF 1.6 4区工程技术

International Journal of Automotive Technology Pub Date : 2024-07-02 DOI: 10.1007/s12239-024-00107-6

Hongnan Wang, Bao Zhang, Nengfeng Xie, Rui Zhou

引用次数: 0

Eco-driving Profile Optimization by Dynamic Programming for Battery Electric Vehicles 通过动态编程优化电池电动汽车的生态驾驶模式

IF 1.6 4区工程技术

International Journal of Automotive Technology Pub Date : 2024-07-01 DOI: 10.1007/s12239-024-00105-8

Dohyun Park, Woong Lee, Jongryeol Jeong, Dominik Karbowski, Namwook Kim

{"title":"Eco-driving Profile Optimization by Dynamic Programming for Battery Electric Vehicles","authors":"Dohyun Park, Woong Lee, Jongryeol Jeong, Dominik Karbowski, Namwook Kim","doi":"10.1007/s12239-024-00105-8","DOIUrl":"https://doi.org/10.1007/s12239-024-00105-8","url":null,"abstract":"Although full automation has not yet been achieved, automated vehicles are a valid research area. Not only would automated vehicles provide ultimate driver convenience, but they would maximize energy efficiency by eliminating undesired human driving behaviors and optimally controlling the powertrain. From the perspective of control related to energy saving, speed profile optimization is important for improving system efficiency and satisfying passenger demands. This study employs Dynamic Programming (DP) to solve the constrained optimal problem for travel time, distance, and speed limit by exploring all possible control options. The solutions obtained by DP demonstrate consistent control patterns combining four control modes—acceleration, cruising, coasting, and braking, with cruising or coasting being selective depending on the boundary conditions. This study introduces DP-based simulation results and attempts to provide comprehensive interpretations of the optimal policy by analyzing the essential factors that affect the control problem, including boundary conditions, road load, and powertrain characteristics. Based on these interpretations, the control concepts can be explained as the optimal policy selecting the best control option based on system efficiency and boundary conditions. The results of DP are compared with a human-like driver model to show that the optimal speed profiles can effectively reduce energy consumption.","PeriodicalId":50338,"journal":{"name":"International Journal of Automotive Technology","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141519599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A New Equation for Fuel Economy of Internal Combustion Engine Vehicles in Republic of Korea Based on 5-Cycle Test 基于 5 循环测试的大韩民国内燃机汽车燃油经济性新公式

IF 1.6 4区工程技术

International Journal of Automotive Technology Pub Date : 2024-06-29 DOI: 10.1007/s12239-024-00110-x

Man Su Noh, Jeong Mo Lee, Dong Yoon Lim, Jin Han Ahn, Ki Bum Kim

引用次数: 0

Improvement of De-NOx Performance of a SCR System by Dual-Point Ammonia Injection in a Diesel Engine 在柴油发动机中通过双点氨喷射改善选择性催化还原系统的脱氮性能

IF 1.6 4区工程技术

International Journal of Automotive Technology Pub Date : 2024-06-28 DOI: 10.1007/s12239-024-00115-6

Hassan Raza, Yanghwa Kim, Ocktaeck Lim, Kwang-Chul Oh, Hongsuk Kim

引用次数: 0

Multi-scale Small Target Detection for Indoor Mobile Rescue Vehicles Based on Improved YOLOv5 基于改进型 YOLOv5 的室内移动救援车多尺度小目标检测

IF 1.6 4区工程技术

International Journal of Automotive Technology Pub Date : 2024-06-27 DOI: 10.1007/s12239-024-00104-9

Maoyue Li, Tenghui Yang, Shengbo Xu, Lingqiang Meng, Zhicheng Liu

{"title":"Multi-scale Small Target Detection for Indoor Mobile Rescue Vehicles Based on Improved YOLOv5","authors":"Maoyue Li, Tenghui Yang, Shengbo Xu, Lingqiang Meng, Zhicheng Liu","doi":"10.1007/s12239-024-00104-9","DOIUrl":"https://doi.org/10.1007/s12239-024-00104-9","url":null,"abstract":"To solve the problems that the YOLOv5 object detection network has low detection accuracy, false detection, and missed detection of small objects for trapped people and medical rescue supplies when there is interference in the light background during indoor rescue, this paper proposes a multi-scale small object detection network multi-scale small YOLOv5s (MS-YOLOv5s). A CAC3 module that integrates the attention mechanism is proposed to capture object feature information in both channel and spatial directions; the neck BiFPN feature pyramid network is improved to improve the model's ability to fuse features of different scales, and the activation function of the convolution module is replaced by SiLU, to improve the adaptive ability of the model for small object detection. The model is deployed on the mobile rescue detection platform. The experimental results show that the mAP @ 0.5 of MS-YOLOV5s is 7.8% and 24.9% higher than that of YOLOv5s at different scales and different postures of trapped people, and the FPS reaches about 12, which can meet the needs of indoor mobile detection, proving the effectiveness of the method proposed in this paper and the robustness of the network model.","PeriodicalId":50338,"journal":{"name":"International Journal of Automotive Technology","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141519600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0