Pub Date : 2024-09-18DOI: 10.1177/09544070241272796
Yasser Fatouh
In this paper, experimental comparison between Simplex and Duplex drum brake units performance for three different drum lining profile designs is carried out. The three linings profiles are normal (no slot), with one slot and with three slots. In this study, brake test rig has been designed to represent the actual braking process environment. Brake oil pressure and drum speed are the operational parameters that are varied during the experimental work. From the experimental work and mathematical models for brake force, brake factor, and final friction temperature, the comparisons were carried out. The final conclusions indicate that lining with one slot profile is the most suitable, since the percentage improvement of mean brake force and brake factor of duplex drum brake (D) linings versus simplex drum brake (S) linings reaching 84.09% and 82.73% higher than three slots lining profile but lower than lining with normal profile at low pressure 5 bar and low speed 50 rpm. Also, the percentage improvement of mean primary shoe final friction temperature reduction for the one slot profile reaches 30.00% higher than normal lining profile but lower than lining with three slots profile at high pressure 20 bar and drum speed 50 rpm.
{"title":"Comparison of simplex and duplex drum brakes linings with transverse slots in vehicles","authors":"Yasser Fatouh","doi":"10.1177/09544070241272796","DOIUrl":"https://doi.org/10.1177/09544070241272796","url":null,"abstract":"In this paper, experimental comparison between Simplex and Duplex drum brake units performance for three different drum lining profile designs is carried out. The three linings profiles are normal (no slot), with one slot and with three slots. In this study, brake test rig has been designed to represent the actual braking process environment. Brake oil pressure and drum speed are the operational parameters that are varied during the experimental work. From the experimental work and mathematical models for brake force, brake factor, and final friction temperature, the comparisons were carried out. The final conclusions indicate that lining with one slot profile is the most suitable, since the percentage improvement of mean brake force and brake factor of duplex drum brake (D) linings versus simplex drum brake (S) linings reaching 84.09% and 82.73% higher than three slots lining profile but lower than lining with normal profile at low pressure 5 bar and low speed 50 rpm. Also, the percentage improvement of mean primary shoe final friction temperature reduction for the one slot profile reaches 30.00% higher than normal lining profile but lower than lining with three slots profile at high pressure 20 bar and drum speed 50 rpm.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":"118 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142263375","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}
Pub Date : 2024-09-17DOI: 10.1177/09544070241277412
Yong Guan, Ning Li, Pengzhan Chen, Yongchao Zhang
In vehicle trajectory prediction, constructing the interactive relationships among vehicles within the traffic environment poses a significant challenge. Existing models predominantly focus on temporal dependencies within vehicle histories and spatial correlations among neighboring vehicles, overlooking the continuous influence of historical vehicle states on the current time step and the interplay of multiple sequences over time. To address these limitations, we propose a method for multimodal vehicle trajectory prediction that integrates Hybrid Time-step Scene Interaction (HTSI) into the spatiotemporal relationships. Firstly, we introduce the HTSI module, comprising Multi-step Temporal Information Aggregation (MTIA) and Single-step Temporal Information Aggregation (STIA) methods. MTIA utilizes multi-head attention mechanisms to capture temporal dependencies between consecutive frames, thereby generating new time series amalgamating the ongoing influence of historical time states on the current timestamp. Simultaneously, STIA employs multi-head attention mechanisms to capture the spatial dimension weights of multiple time series and, by aggregating spatial interaction features at each timestamp, generates new time series fused with spatial interaction influences. Subsequently, feature extraction is performed through LSTM layers. Moreover, we propose an improved DIPM pooling module, improving the model’s long-term prediction capability by selectively reusing historical hidden states. Ultimately, based on training results from the HighD and NGSIM datasets, our model demonstrates significant advantages in long-term prediction compared to other state-of-the-art trajectory prediction models. Specifically, within the 5 s prediction window, the model achieved a root mean square error (RMSE) of 2.79 m on the NGSIM dataset, representing a 33.62% improvement over the baseline model’s average accuracy. Additionally, on the HighD dataset, the model attained an RMSE of 2.16 m, reflecting a 33.43% enhancement. The crucial code can be obtained from the provided link: https://github.com/gyhhq/Prediction-trajectory .
{"title":"Vehicle trajectory prediction method integrating spatiotemporal relationships with hybrid time-step scene interaction","authors":"Yong Guan, Ning Li, Pengzhan Chen, Yongchao Zhang","doi":"10.1177/09544070241277412","DOIUrl":"https://doi.org/10.1177/09544070241277412","url":null,"abstract":"In vehicle trajectory prediction, constructing the interactive relationships among vehicles within the traffic environment poses a significant challenge. Existing models predominantly focus on temporal dependencies within vehicle histories and spatial correlations among neighboring vehicles, overlooking the continuous influence of historical vehicle states on the current time step and the interplay of multiple sequences over time. To address these limitations, we propose a method for multimodal vehicle trajectory prediction that integrates Hybrid Time-step Scene Interaction (HTSI) into the spatiotemporal relationships. Firstly, we introduce the HTSI module, comprising Multi-step Temporal Information Aggregation (MTIA) and Single-step Temporal Information Aggregation (STIA) methods. MTIA utilizes multi-head attention mechanisms to capture temporal dependencies between consecutive frames, thereby generating new time series amalgamating the ongoing influence of historical time states on the current timestamp. Simultaneously, STIA employs multi-head attention mechanisms to capture the spatial dimension weights of multiple time series and, by aggregating spatial interaction features at each timestamp, generates new time series fused with spatial interaction influences. Subsequently, feature extraction is performed through LSTM layers. Moreover, we propose an improved DIPM pooling module, improving the model’s long-term prediction capability by selectively reusing historical hidden states. Ultimately, based on training results from the HighD and NGSIM datasets, our model demonstrates significant advantages in long-term prediction compared to other state-of-the-art trajectory prediction models. Specifically, within the 5 s prediction window, the model achieved a root mean square error (RMSE) of 2.79 m on the NGSIM dataset, representing a 33.62% improvement over the baseline model’s average accuracy. Additionally, on the HighD dataset, the model attained an RMSE of 2.16 m, reflecting a 33.43% enhancement. The crucial code can be obtained from the provided link: https://github.com/gyhhq/Prediction-trajectory .","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":"124 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142263376","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}
Pub Date : 2024-09-17DOI: 10.1177/09544070241272761
Liang Tao, Yangguang Cui, Xiaodong Zhang, Wenfeng Shen, Weijia Lu
In recent years, Federated Learning (FL) has attracted much attention in Vehicle Trajectory Prediction (VTP) as it can resolve the critical issues of insufficient data, data privacy, and training efficiency. However, compared with centralized training, the model trained by FL may have insufficient prediction performance. This important issue comes from a statistical heterogeneity distribution of the local data in the participating clients, that is, non-IID. Therefore, this paper introduces a Clustered Federated Learning (CFL) approach for the VTP model to mitigate the influence of non-IID data. The proposed approach consists of federated trajectory clustering and federated VTP model training. In federated trajectory clustering, the optimal trajectory scenario discriminator is produced using federated K-means clustering without direct access to private data. In the federated VTP model training, multiple VTP models for specific trajectory scenarios are trained to deal with the influence of non-IID data. Experimental results reveal that our approach outperforms the state-of-the-art FL method on both NGSIM and HighD datasets, achieving up to 13.82% convergence acceleration and 12.47% RMSE reduction.
{"title":"Scenario-aware clustered federated learning for vehicle trajectory prediction with non-IID data","authors":"Liang Tao, Yangguang Cui, Xiaodong Zhang, Wenfeng Shen, Weijia Lu","doi":"10.1177/09544070241272761","DOIUrl":"https://doi.org/10.1177/09544070241272761","url":null,"abstract":"In recent years, Federated Learning (FL) has attracted much attention in Vehicle Trajectory Prediction (VTP) as it can resolve the critical issues of insufficient data, data privacy, and training efficiency. However, compared with centralized training, the model trained by FL may have insufficient prediction performance. This important issue comes from a statistical heterogeneity distribution of the local data in the participating clients, that is, non-IID. Therefore, this paper introduces a Clustered Federated Learning (CFL) approach for the VTP model to mitigate the influence of non-IID data. The proposed approach consists of federated trajectory clustering and federated VTP model training. In federated trajectory clustering, the optimal trajectory scenario discriminator is produced using federated K-means clustering without direct access to private data. In the federated VTP model training, multiple VTP models for specific trajectory scenarios are trained to deal with the influence of non-IID data. Experimental results reveal that our approach outperforms the state-of-the-art FL method on both NGSIM and HighD datasets, achieving up to 13.82% convergence acceleration and 12.47% RMSE reduction.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":"189 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142263374","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}
Amidst the rapid progression of the road transport industry, the safety and efficiency of heavy-vehicle platoons have garnered significant attention. The study tackles the challenge of obstacle avoidance presented by vehicles owing to their considerable mass, delayed response times, and line-of-sight impediments, by introducing a cooperative obstacle avoidance system for heavy-vehicle platoons based on deep reinforcement learning. The system comprises three primary modules: perception, decision-making, and control. Initially, the perception module acquires real-time environmental data. Subsequently, the decision-making module formulates obstacle avoidance decisions based on the acquired data. Specifically, it implements a two-stage braking obstacle avoidance strategy under low collision risk scenarios, while employing a fifth-degree polynomial for planning and tracking obstacle avoidance paths under high collision risk conditions suitable for steering maneuvers. The control module utilizes the local multi-agent deep deterministic policy gradient (LADDPG) algorithm to train the heavy-vehicle platoon agents, ensuring the formation’s maintenance while mitigating collisions with other vehicles and obstacles. The effectiveness of the proposed system is substantiated through simulation experiments, demonstrating its adaptability to various traffic conditions, selection of suitable obstacle avoidance strategies, and significant enhancement of obstacle avoidance performance and heavy-vehicle platoon stability.
{"title":"Research on Obstacle Avoidance Strategy of Automated Heavy Vehicle Platoon in High-Speed Scenarios","authors":"Yingfeng Cai, Lili Zhan, Xiaoqiang Sun, Yubo Lian, Youguo He, Long Chen","doi":"10.1177/09544070241276062","DOIUrl":"https://doi.org/10.1177/09544070241276062","url":null,"abstract":"Amidst the rapid progression of the road transport industry, the safety and efficiency of heavy-vehicle platoons have garnered significant attention. The study tackles the challenge of obstacle avoidance presented by vehicles owing to their considerable mass, delayed response times, and line-of-sight impediments, by introducing a cooperative obstacle avoidance system for heavy-vehicle platoons based on deep reinforcement learning. The system comprises three primary modules: perception, decision-making, and control. Initially, the perception module acquires real-time environmental data. Subsequently, the decision-making module formulates obstacle avoidance decisions based on the acquired data. Specifically, it implements a two-stage braking obstacle avoidance strategy under low collision risk scenarios, while employing a fifth-degree polynomial for planning and tracking obstacle avoidance paths under high collision risk conditions suitable for steering maneuvers. The control module utilizes the local multi-agent deep deterministic policy gradient (LADDPG) algorithm to train the heavy-vehicle platoon agents, ensuring the formation’s maintenance while mitigating collisions with other vehicles and obstacles. The effectiveness of the proposed system is substantiated through simulation experiments, demonstrating its adaptability to various traffic conditions, selection of suitable obstacle avoidance strategies, and significant enhancement of obstacle avoidance performance and heavy-vehicle platoon stability.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":"47 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142269402","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}
This paper is concerned with the optimal control strategies for the longitudinal control, powertrain, and air conditioning (A/C) system of connected four-wheel hub-drive electric vehicles (EVs). A hierarchical control framework is developed to enhance the energy economy of the vehicle. Real-time connected information is utilized in the upper layer to determine the travel mode. Then, a multi-objective motion planning system (MOMPS) is proposed to plan the optimal acceleration trajectory. In the lower layer, an offline global optimization approach is employed to find the torque combinations that minimize the total power loss. The proposed A/C controller operates based on the bi-level model predictive control (Bi-level MPC) algorithm. A novel prediction model is developed to enable the A/C system to decrease energy consumption by leveraging the speed of the vehicle. The performance of the MOMPS is evaluated using urban test road data, demonstrating that the MOMPS can balance multiple objectives compared to global dynamic programing (Global DP) and the intelligent driver model (IDM). In addition, the proposed torque distribution strategy results in a 4.98% energy-savings rate through comparison with the even torque distribution strategy. Moreover, the A/C controller proposed in this paper can optimize energy consumption by 13.57% compared to a baseline strategy that maintains a constant setting.
{"title":"Cooperative energy optimal control involving optimization of longitudinal motion, powertrain, and air conditioning systems","authors":"Yanbei Zhang, Mingliang Wei, Meilin Ren, Chongfan Liu, Mengwei Han, Jingyu Zhu","doi":"10.1177/09544070241272899","DOIUrl":"https://doi.org/10.1177/09544070241272899","url":null,"abstract":"This paper is concerned with the optimal control strategies for the longitudinal control, powertrain, and air conditioning (A/C) system of connected four-wheel hub-drive electric vehicles (EVs). A hierarchical control framework is developed to enhance the energy economy of the vehicle. Real-time connected information is utilized in the upper layer to determine the travel mode. Then, a multi-objective motion planning system (MOMPS) is proposed to plan the optimal acceleration trajectory. In the lower layer, an offline global optimization approach is employed to find the torque combinations that minimize the total power loss. The proposed A/C controller operates based on the bi-level model predictive control (Bi-level MPC) algorithm. A novel prediction model is developed to enable the A/C system to decrease energy consumption by leveraging the speed of the vehicle. The performance of the MOMPS is evaluated using urban test road data, demonstrating that the MOMPS can balance multiple objectives compared to global dynamic programing (Global DP) and the intelligent driver model (IDM). In addition, the proposed torque distribution strategy results in a 4.98% energy-savings rate through comparison with the even torque distribution strategy. Moreover, the A/C controller proposed in this paper can optimize energy consumption by 13.57% compared to a baseline strategy that maintains a constant setting.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":"74 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142263377","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}
Pub Date : 2024-09-14DOI: 10.1177/09544070241280744
Hechao Zhou, Zhengyang Wan, Mingsu Mei, Jimin Zhang, Markus Hecht
The Virtual Track Train (VTT) represents a novel urban transportation solution that combines elements of both road and rail vehicles. Currently, VTT has gained significant adoption in several cities in China including Yibin, Zhuzhou, Harbin, and Yancheng. Despite its growing usage, the unique structure and complex tire-ground interaction of VTT pose significant challenges in terms of tire wear, which has become a pressing issue. This study develops and validates a multi-body dynamics model of VTT along with a finite element model of its tire. The tire-ground contact behavior and boundary conditions are studied from various perspectives to calculate tire wear. The simulation results demonstrate that the internal pressure of the tires, the load of VTT, the pavement conditions, the inclination angle, and slippage of tires all have critical effects on VTT’s tire wear. These findings suggest that the operating conditions of VTT must be carefully managed to reduce tire wear and ensure safe operation. Furthermore, the research results of tire wear mechanism of VTT offers valuable insights for the optimization and maintenance of VTT.
{"title":"Study of the tire wear of virtual track train","authors":"Hechao Zhou, Zhengyang Wan, Mingsu Mei, Jimin Zhang, Markus Hecht","doi":"10.1177/09544070241280744","DOIUrl":"https://doi.org/10.1177/09544070241280744","url":null,"abstract":"The Virtual Track Train (VTT) represents a novel urban transportation solution that combines elements of both road and rail vehicles. Currently, VTT has gained significant adoption in several cities in China including Yibin, Zhuzhou, Harbin, and Yancheng. Despite its growing usage, the unique structure and complex tire-ground interaction of VTT pose significant challenges in terms of tire wear, which has become a pressing issue. This study develops and validates a multi-body dynamics model of VTT along with a finite element model of its tire. The tire-ground contact behavior and boundary conditions are studied from various perspectives to calculate tire wear. The simulation results demonstrate that the internal pressure of the tires, the load of VTT, the pavement conditions, the inclination angle, and slippage of tires all have critical effects on VTT’s tire wear. These findings suggest that the operating conditions of VTT must be carefully managed to reduce tire wear and ensure safe operation. Furthermore, the research results of tire wear mechanism of VTT offers valuable insights for the optimization and maintenance of VTT.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":"30 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142263378","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}
Pub Date : 2024-09-14DOI: 10.1177/09544070241276031
Hui Liu, Qi Yan, Pu Gao, Keyu Yan, Yunkun Xie
The Operational Transfer Path Analysis (OTPA) is widely used to analyze signal transfer paths in various fields, but its applications in gear transmission systems are limited. In this paper, the OTPA method is appropriately applied to the study of vibration signal transfer paths of fixed shaft gear transmission systems. Firstly, the dynamic model of a three-axis two-stage fixed-shaft gear transmission system is developed. This model takes into account factors such as the impact of dynamic center distance on backlash and provides a comprehensive analysis of time-varying meshing stiffness and forces. Experiments are conducted to verify the accuracy of the model. Subsequently, this paper delves into the OTPA process for solving the signal transfer coefficient matrix. It also derives the calculation method for computing the contribution of signal transfer paths, which provides a theoretical basis for establishing the evaluation mechanism of the signal transfer paths. Next, the gear transmission system’s signal transfer is analyzed based on the OTPA method, and the contribution of each path is computed. The dominant path is identified by ranking the contribution of these paths. Finally, the excitation experiment of a single signal transfer path reveals the essence of the signal transfer mechanism. This research contributes to a deeper understanding of signal transfer paths within gear transmission systems based on the OTPA method, it identifies the optimal distribution of sensor installation positions for fault signal diagnosis, paving the way for more effective fault detection and diagnosis in the gear transmission system.
{"title":"Operational transfer path analysis for the fixed shaft gear transmission system based on the simulation and experiment","authors":"Hui Liu, Qi Yan, Pu Gao, Keyu Yan, Yunkun Xie","doi":"10.1177/09544070241276031","DOIUrl":"https://doi.org/10.1177/09544070241276031","url":null,"abstract":"The Operational Transfer Path Analysis (OTPA) is widely used to analyze signal transfer paths in various fields, but its applications in gear transmission systems are limited. In this paper, the OTPA method is appropriately applied to the study of vibration signal transfer paths of fixed shaft gear transmission systems. Firstly, the dynamic model of a three-axis two-stage fixed-shaft gear transmission system is developed. This model takes into account factors such as the impact of dynamic center distance on backlash and provides a comprehensive analysis of time-varying meshing stiffness and forces. Experiments are conducted to verify the accuracy of the model. Subsequently, this paper delves into the OTPA process for solving the signal transfer coefficient matrix. It also derives the calculation method for computing the contribution of signal transfer paths, which provides a theoretical basis for establishing the evaluation mechanism of the signal transfer paths. Next, the gear transmission system’s signal transfer is analyzed based on the OTPA method, and the contribution of each path is computed. The dominant path is identified by ranking the contribution of these paths. Finally, the excitation experiment of a single signal transfer path reveals the essence of the signal transfer mechanism. This research contributes to a deeper understanding of signal transfer paths within gear transmission systems based on the OTPA method, it identifies the optimal distribution of sensor installation positions for fault signal diagnosis, paving the way for more effective fault detection and diagnosis in the gear transmission system.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":"25 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142263379","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}
Pub Date : 2024-09-14DOI: 10.1177/09544070241280403
Wei Li, Mingxi Shao, Yuefeng Du, Zhixiang Li, Zhijuan Sun, Fan Yang
An automatic navigation system aiming at improving the accuracy and efficiency of a large high clearance self-propelled sprayer was developed. First, a navigation hydraulic steering system was designed according to the structural characteristics and operation requirements of the sprayer, and a mathematical model of the system was established to describe the working characteristics of the navigation system. The system includes a navigation control strategy, a pure pursuit path tracking algorithm, and a fuzzy adaptive proportional-integral-derivative control method. To verify the performance of the system, a simulation model was developed using MATLAB/Simulink, and the performance of the control methods were compared. Additionally, an actual vehicle test platform was built based on 3WPG-3000 high clearance self-propelled sprayer independently developed by the research group. The simulation results revealed that under the two-wheel steering mode, the lateral position deviation of the vehicle decreases to 0 m in 11 s, and the heading angle deviation decreases to 0 rad in about 11 s; while under four-wheel steering mode, the lateral position deviation of the vehicle decreases to 0 m in 8 s, and the heading angle deviation decreases to 0 rad in 8 s. The field test results revealed that at the speed of 3 km/h, the sprayer tracked the target path in 5.84 s under the two-wheel steering mode and reached stability, and tracked the target path in 4.08 s under the four-wheel steering mode and reached stability; while at the speed of 5 km/h, the spray tracked the target path in 3.75 s under the four-wheel steering mode and reached stability. Altogether, the results of the simulation and field test verify the stability, accuracy, and practicability of the system.
开发了一种自动导航系统，旨在提高大型高净空自走式喷雾器的精度和效率。首先，根据喷雾器的结构特点和操作要求设计了导航液压转向系统，并建立了系统数学模型来描述导航系统的工作特性。该系统包括导航控制策略、纯追求路径跟踪算法和模糊自适应比例-积分-派生控制方法。为了验证系统的性能，使用 MATLAB/Simulink 开发了一个仿真模型，并比较了各种控制方法的性能。此外，还以课题组自主研发的 3WPG-3000 型高净空自走式喷雾器为基础，搭建了实车试验平台。仿真结果表明，在两轮转向模式下，车辆的横向位置偏差在 11 s 内减小到 0 m，航向角偏差在约 11 s 内减小到 0 rad；而在四轮转向模式下，车辆的横向位置偏差在 8 s 内减小到 0 m，航向角偏差在 8 s 内减小到 0 rad。实地测试结果表明，在 3 km/h 的速度下，喷雾器在两轮转向模式下 5.84 s 内跟踪目标路径并达到稳定，在四轮转向模式下 4.08 s 内跟踪目标路径并达到稳定；而在 5 km/h 的速度下，喷雾器在四轮转向模式下 3.75 s 内跟踪目标路径并达到稳定。总之，模拟和实地测试的结果验证了该系统的稳定性、准确性和实用性。
{"title":"Design and verification of automatic navigation control system for large high clearance self-propelled sprayer","authors":"Wei Li, Mingxi Shao, Yuefeng Du, Zhixiang Li, Zhijuan Sun, Fan Yang","doi":"10.1177/09544070241280403","DOIUrl":"https://doi.org/10.1177/09544070241280403","url":null,"abstract":"An automatic navigation system aiming at improving the accuracy and efficiency of a large high clearance self-propelled sprayer was developed. First, a navigation hydraulic steering system was designed according to the structural characteristics and operation requirements of the sprayer, and a mathematical model of the system was established to describe the working characteristics of the navigation system. The system includes a navigation control strategy, a pure pursuit path tracking algorithm, and a fuzzy adaptive proportional-integral-derivative control method. To verify the performance of the system, a simulation model was developed using MATLAB/Simulink, and the performance of the control methods were compared. Additionally, an actual vehicle test platform was built based on 3WPG-3000 high clearance self-propelled sprayer independently developed by the research group. The simulation results revealed that under the two-wheel steering mode, the lateral position deviation of the vehicle decreases to 0 m in 11 s, and the heading angle deviation decreases to 0 rad in about 11 s; while under four-wheel steering mode, the lateral position deviation of the vehicle decreases to 0 m in 8 s, and the heading angle deviation decreases to 0 rad in 8 s. The field test results revealed that at the speed of 3 km/h, the sprayer tracked the target path in 5.84 s under the two-wheel steering mode and reached stability, and tracked the target path in 4.08 s under the four-wheel steering mode and reached stability; while at the speed of 5 km/h, the spray tracked the target path in 3.75 s under the four-wheel steering mode and reached stability. Altogether, the results of the simulation and field test verify the stability, accuracy, and practicability of the system.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":"16 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142269903","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}
Pub Date : 2024-09-14DOI: 10.1177/09544070241272795
Jiangqi Long, Zhe Kong, Jianhong Zhang
The investigation of magnetorheological (MR) semi-active suspension is crucial for automotive applications. This paper introduces a novel approach by considering time delay effect when load changes and considering vehicle’s spring-loaded mass as an uncertain parameter. To address these challenges, a new magnetorheological semi-active quarter-vehicle suspension controller is proposed. Controller combines inverse model with Taylor series backstepping control strategy to determine the necessary damping force provided by magnetorheological damper based on system’s dynamic error. Additionally, damping force is compensated using Taylor series expansion method. Drive current of magnetorheological damper is obtained by solving hyperbolic positive model parameters and inverse model through nonlinear least squares genetic algorithm. Simulation experiments are conducted to compare the performance of Taylor series backstepping control (TBS) suspension, backstepping control suspension affected by time delay, MSH control suspension affected by time delay and passive suspension. Various metrics such as spring-loaded mass displacement, velocity, acceleration, suspension dynamic displacement, and wheel dynamic load under random road excitation are evaluated. Simulation results demonstrate that proposed system effectively mitigates vehicle vibration caused by time delay and load variations, while enhancing vehicle’s handling and smoothness.
{"title":"Research on time delay compensation control of Taylor series backstepping for magnetorheological semi-active suspension","authors":"Jiangqi Long, Zhe Kong, Jianhong Zhang","doi":"10.1177/09544070241272795","DOIUrl":"https://doi.org/10.1177/09544070241272795","url":null,"abstract":"The investigation of magnetorheological (MR) semi-active suspension is crucial for automotive applications. This paper introduces a novel approach by considering time delay effect when load changes and considering vehicle’s spring-loaded mass as an uncertain parameter. To address these challenges, a new magnetorheological semi-active quarter-vehicle suspension controller is proposed. Controller combines inverse model with Taylor series backstepping control strategy to determine the necessary damping force provided by magnetorheological damper based on system’s dynamic error. Additionally, damping force is compensated using Taylor series expansion method. Drive current of magnetorheological damper is obtained by solving hyperbolic positive model parameters and inverse model through nonlinear least squares genetic algorithm. Simulation experiments are conducted to compare the performance of Taylor series backstepping control (TBS) suspension, backstepping control suspension affected by time delay, MSH control suspension affected by time delay and passive suspension. Various metrics such as spring-loaded mass displacement, velocity, acceleration, suspension dynamic displacement, and wheel dynamic load under random road excitation are evaluated. Simulation results demonstrate that proposed system effectively mitigates vehicle vibration caused by time delay and load variations, while enhancing vehicle’s handling and smoothness.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":"194 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142263418","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}
Pub Date : 2024-09-10DOI: 10.1177/09544070241273983
Yawei Zhu, Yi Zhang, Liping Xie, Zhien Liu, Chihua Lu
The sound characteristic is a critical metric to manifest the brand differentiation of electric vehicle (EV), and the sound design with more diverse acoustic characteristics has become a hot issue in current research of EV technology. In this paper, an efficient technique of active sound design (ASD) is explored to develop the control system of active sound generation (ASG) with powerful sound quality for EV. Firstly, an optimization algorithm of sound synthesis based on multi-frequency superimposition is proposed to improve the harmonic interference phenomenon in the synthesized sounds. Subsequently, an adaptive sound control strategy is formulated, where an iterative accumulation method is proposed to calculate the “virtual engine speed” of EV, and a gain table is presented to divide the running state. Besides, an ASG system is developed based on the proposed ASD technique. The tests result demonstrate that there are 18 target order sounds are reproduced perfectly, and the powerful sound quality interior EV is enhanced while the original interior acoustic environment of EV is retained, which confirms the effectiveness of the proposed control technique of ASG system. The proposed ASD technique here accelerates the change from silence to sound quality in the electric vehicles, which has important theoretical significance and engineering value.
{"title":"An efficient technique for developing the active sound control system in electric vehicle","authors":"Yawei Zhu, Yi Zhang, Liping Xie, Zhien Liu, Chihua Lu","doi":"10.1177/09544070241273983","DOIUrl":"https://doi.org/10.1177/09544070241273983","url":null,"abstract":"The sound characteristic is a critical metric to manifest the brand differentiation of electric vehicle (EV), and the sound design with more diverse acoustic characteristics has become a hot issue in current research of EV technology. In this paper, an efficient technique of active sound design (ASD) is explored to develop the control system of active sound generation (ASG) with powerful sound quality for EV. Firstly, an optimization algorithm of sound synthesis based on multi-frequency superimposition is proposed to improve the harmonic interference phenomenon in the synthesized sounds. Subsequently, an adaptive sound control strategy is formulated, where an iterative accumulation method is proposed to calculate the “virtual engine speed” of EV, and a gain table is presented to divide the running state. Besides, an ASG system is developed based on the proposed ASD technique. The tests result demonstrate that there are 18 target order sounds are reproduced perfectly, and the powerful sound quality interior EV is enhanced while the original interior acoustic environment of EV is retained, which confirms the effectiveness of the proposed control technique of ASG system. The proposed ASD technique here accelerates the change from silence to sound quality in the electric vehicles, which has important theoretical significance and engineering value.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":"6 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142205276","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}
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