{"title":"Reviewers","authors":"Peijun Xu","doi":"10.4271/10-07-04-0036","DOIUrl":"https://doi.org/10.4271/10-07-04-0036","url":null,"abstract":"<div>Reviewers</div>","PeriodicalId":42978,"journal":{"name":"SAE International Journal of Vehicle Dynamics Stability and NVH","volume":"46 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134905904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Justus Raabe, Fabian Fontana, Jens Neubeck, Andreas Wagner
{"title":"Contribution to the Objective Evaluation of Combined Longitudinal and Lateral Vehicle Dynamics in Nonlinear Driving Range","authors":"Justus Raabe, Fabian Fontana, Jens Neubeck, Andreas Wagner","doi":"10.4271/10-07-04-0034","DOIUrl":"https://doi.org/10.4271/10-07-04-0034","url":null,"abstract":"<div>Since the complexity of modern vehicles is increasing continuously, car manufacturers are forced to improve the efficiency of their development process to remain profitable. A frequently mentioned measure is the consequent integration of virtual methods. In this regard, objective evaluation criteria are essential for the virtual design of driving dynamics. Therefore, this article aims to identify robust objective evaluation criteria for the nonlinear combined longitudinal and lateral dynamics of a vehicle. The article focuses on the acceleration in a turn maneuver since available objective criteria do not consider all relevant characteristics of vehicle dynamics. For the identification of the objective criteria, a generic method is developed and applied. First, an open-loop test procedure and a set of potential robust objective criteria are defined. Subsequently, suitable criteria are selected for different vehicle dynamics characteristics based on an investigation of Pearson correlations between the objective criteria and established subjective rating criteria. For this purpose, a subjective evaluation study with six specifically selected vehicle variants is conducted. Finally, the applicability of the selected objective criteria for vehicles of different segments is assessed through a benchmark of current vehicles. The results are objective criteria for the vehicle characteristics driving stability, oversteer/understeer, and traction. In contrast to existing objective criteria, the identified criteria shows a high robustness to measurement noise. Furthermore, there is a comprehensible correlation to established subjective rating criteria for each objective criterion. Lastly, the benchmark of current vehicles proves the applicability of the identified criteria.</div>","PeriodicalId":42978,"journal":{"name":"SAE International Journal of Vehicle Dynamics Stability and NVH","volume":"195 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135779525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Active Vibration Control of Electric Drive System in Electric Vehicles Based on Active Disturbance Rejection Current Compensation under Impact Conditions","authors":"Shuaishuai Ge, Shuang Hou, Yufan Yang, Zhigang Zhang, Fang Tang","doi":"10.4271/10-07-04-0033","DOIUrl":"https://doi.org/10.4271/10-07-04-0033","url":null,"abstract":"<div>To address the torsional vibration caused by impact conditions in electric vehicles (EVs), such as deceleration belts and road irregularities, a comprehensive electromechanical coupling dynamics model is developed. This model includes the dynamic behavior of the permanent magnet synchronous motor (PMSM) and the gear transmission system in the EV’s electric drive system. The study aims to investigate the electromechanical coupling dynamics and vibration characteristics of the system under impact conditions. Based on this, an innovative active damping control strategy is proposed for the EV’s electric drive system when subjected to impact conditions. This strategy incorporates active disturbance rejection current compensation (ADRCC) to achieve a speed difference of zero at two ends of the half-shaft as the tracking control target, and compensating current is superimposed on the original given current of the motor controller. The results highlight the effectiveness of the proposed strategy. Under single-pulse impact condition, the vibration energy of the gear transmission system is reduced by approximately 63.1% compared to without the controller. Under continuous impact conditions, the vibration energy of the gear transmission system is reduced by approximately 55.63% and the cumulative error of the speed difference is reduced by approximately 61.4% compared to without the controller. These findings demonstrate that the proposed strategy successfully suppresses the continuous oscillation of the electric drive system under impact conditions. The research results provide a theoretical reference for the vibration suppression of the electric drive system of EVs.</div>","PeriodicalId":42978,"journal":{"name":"SAE International Journal of Vehicle Dynamics Stability and NVH","volume":"184 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136033672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ahmed Shehata Gad, Syeda Darakhshan Jabeen, Wael Galal Ata
{"title":"Damping Magnetorheological Systems Based on Optimal Neural Networks Preview Control Integrated with New Hybrid Fuzzy Controller to Improve Ride Comfort","authors":"Ahmed Shehata Gad, Syeda Darakhshan Jabeen, Wael Galal Ata","doi":"10.4271/10-07-04-0032","DOIUrl":"https://doi.org/10.4271/10-07-04-0032","url":null,"abstract":"<div>Adaptive neural networks (ANNs) have become famous for modeling and controlling dynamic systems. However, because of their failure to precisely reflect the intricate dynamics of the system, these have limited use in practical applications and perform poorly during training and testing. This research explores novel approaches to this issue, including modifying the simple neuron unit and developing a generalized neuron (GN). The revised version of the neuron unit helps to develop the system controller, which is responsible for providing the desired control signal based on the inputs received from the dynamic responses of the vehicle suspension system. The controller is then tested and evaluated based on the performance of the magnetorheological (MR) damper for the main suspension system. These results of the tests show that the optimal preview controller designed using the GN both ∑-Π-ANN and Π-∑-ANN can accurately capture the complex dynamics of the MR damper and improve their damping characteristics compared with other methods. The seat and main suspension systems work together to provide more support and comfort for the driver and passengers. The short stroke of the MR damper is used in seat suspension as it allows for more precise control over the suspension and can provide a smoother ride. The new hybrid fuzzy type-2 (T-2) control is designed to accurately estimate the desired damping force for the seat MR damper. This system also allows for the damping force to be adjusted to meet the desired requirements of the seat MR damper. This integration of damping systems allows better control and stability of the vehicle and provides a smoother ride for drivers and passengers. Furthermore, integrating the damping systems increases the overall performance of the vehicle, making it better able to handle various road conditions.</div>","PeriodicalId":42978,"journal":{"name":"SAE International Journal of Vehicle Dynamics Stability and NVH","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135745852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Letter from the Special Issue Editors","authors":"Valentin Ivanov, Dzmitry Savitski","doi":"10.4271/10-07-03-0016","DOIUrl":"https://doi.org/10.4271/10-07-03-0016","url":null,"abstract":"<div>Letter from the Special Issue Editors</div>","PeriodicalId":42978,"journal":{"name":"SAE International Journal of Vehicle Dynamics Stability and NVH","volume":"204 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135392968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Robust Multiagent Reinforcement Learning toward Coordinated\u0000 Decision-Making of Automated Vehicles","authors":"Xiangkun He, Hao Chen, Chengqi Lv","doi":"10.4271/10-07-04-0031","DOIUrl":"https://doi.org/10.4271/10-07-04-0031","url":null,"abstract":"Automated driving is essential for developing and deploying intelligent\u0000 transportation systems. However, unavoidable sensor noises or perception errors\u0000 may cause an automated vehicle to adopt suboptimal driving policies or even lead\u0000 to catastrophic failures. Additionally, the automated driving longitudinal and\u0000 lateral decision-making behaviors (e.g., driving speed and lane changing\u0000 decisions) are coupled, that is, when one of them is perturbed by unknown\u0000 external disturbances, it causes changes or even performance degradation in the\u0000 other. The presence of both challenges significantly curtails the potential of\u0000 automated driving. Here, to coordinate the longitudinal and lateral driving\u0000 decisions of an automated vehicle while ensuring policy robustness against\u0000 observational uncertainties, we propose a novel robust coordinated\u0000 decision-making technique via robust multiagent reinforcement learning.\u0000 Specifically, the automated driving longitudinal and lateral decisions under\u0000 observational perturbations are modeled as a constrained robust multiagent\u0000 Markov decision process. Meanwhile, a nonlinear constraint setting with\u0000 Kullback–Leibler divergence is developed to keep the variation of the driving\u0000 policy perturbed by stochastic perturbations within bounds. Additionally, a\u0000 robust multiagent policy optimization approach is proposed to approximate the\u0000 optimal robust coordinated driving policy. Finally, we evaluate the proposed\u0000 robust coordinated decision-making method in three highway scenarios with\u0000 different traffic densities. Quantitatively, in the absence of noises, the\u0000 proposed method achieves an approximate average enhancement of 25.58% in traffic\u0000 efficiency and 91.31% in safety compared to all baselines across the three\u0000 scenarios. In the presence of noises, our technique improves traffic efficiency\u0000 and safety by an approximate average of 30.81% and 81.02% compared to all\u0000 baselines in the three scenarios, respectively. The results demonstrate that the\u0000 proposed approach is capable of improving automated driving performance and\u0000 ensuring policy robustness against observational uncertainties.","PeriodicalId":42978,"journal":{"name":"SAE International Journal of Vehicle Dynamics Stability and NVH","volume":"69 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78809020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}