{"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
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.
{"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}
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.
{"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
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.
{"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}
Automated driving is essential for developing and deploying intelligent transportation systems. However, unavoidable sensor noises or perception errors may cause an automated vehicle to adopt suboptimal driving policies or even lead to catastrophic failures. Additionally, the automated driving longitudinal and lateral decision-making behaviors (e.g., driving speed and lane changing decisions) are coupled, that is, when one of them is perturbed by unknown external disturbances, it causes changes or even performance degradation in the other. The presence of both challenges significantly curtails the potential of automated driving. Here, to coordinate the longitudinal and lateral driving decisions of an automated vehicle while ensuring policy robustness against observational uncertainties, we propose a novel robust coordinated decision-making technique via robust multiagent reinforcement learning. Specifically, the automated driving longitudinal and lateral decisions under observational perturbations are modeled as a constrained robust multiagent Markov decision process. Meanwhile, a nonlinear constraint setting with Kullback–Leibler divergence is developed to keep the variation of the driving policy perturbed by stochastic perturbations within bounds. Additionally, a robust multiagent policy optimization approach is proposed to approximate the optimal robust coordinated driving policy. Finally, we evaluate the proposed robust coordinated decision-making method in three highway scenarios with different traffic densities. Quantitatively, in the absence of noises, the proposed method achieves an approximate average enhancement of 25.58% in traffic efficiency and 91.31% in safety compared to all baselines across the three scenarios. In the presence of noises, our technique improves traffic efficiency and safety by an approximate average of 30.81% and 81.02% compared to all baselines in the three scenarios, respectively. The results demonstrate that the proposed approach is capable of improving automated driving performance and ensuring policy robustness against observational uncertainties.
{"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}
To investigate the effect of a tire blowout (TBO) on the dynamics of the vehicle comprehensively, a three-dimensional full-vehicle multibody mathematical model is developed and integrated with the nonlinear Dugoff’s tire model. In order to ensure the validity of the developed model, a series of standard maneuvers is carried out and the resulting response is verified using the high-fidelity MSC Adams package. Consequently, the in-plane, as well as out-of-plane dynamics of the vehicle, is extensively examined through a sequence of TBO scenarios with various blown tires and during both rectilinear and curvilinear motion. Moreover, the different possible inputs from the driver, the road bank angle, and the antiroll bar have been accounted for. The results show that the dynamic behavior of the vehicle is tremendously affected both in-plane and out-of-plane and its directional stability is degraded. It has been also found that a vehicle subjected to a TBO accident is prone to a fatal rollover accident due to the excessive lateral acceleration triggered by the TBO. Furthermore, the reaction from the driver plays a crucial role in stabilizing/destabilizing the vehicle following a TBO.
{"title":"Three-Dimensional In-Depth Dynamic Analysis of a Ground Vehicle\u0000 Experiencing a Tire Blowout","authors":"Mahdi Al Quran, Abdel Ra’ouf Mayyas","doi":"10.4271/10-07-04-0030","DOIUrl":"https://doi.org/10.4271/10-07-04-0030","url":null,"abstract":"To investigate the effect of a tire blowout (TBO) on the dynamics of the vehicle\u0000 comprehensively, a three-dimensional full-vehicle multibody mathematical model\u0000 is developed and integrated with the nonlinear Dugoff’s tire model. In order to\u0000 ensure the validity of the developed model, a series of standard maneuvers is\u0000 carried out and the resulting response is verified using the high-fidelity MSC\u0000 Adams package. Consequently, the in-plane, as well as out-of-plane dynamics of\u0000 the vehicle, is extensively examined through a sequence of TBO scenarios with\u0000 various blown tires and during both rectilinear and curvilinear motion.\u0000 Moreover, the different possible inputs from the driver, the road bank angle,\u0000 and the antiroll bar have been accounted for. The results show that the dynamic\u0000 behavior of the vehicle is tremendously affected both in-plane and out-of-plane\u0000 and its directional stability is degraded. It has been also found that a vehicle\u0000 subjected to a TBO accident is prone to a fatal rollover accident due to the\u0000 excessive lateral acceleration triggered by the TBO. Furthermore, the reaction\u0000 from the driver plays a crucial role in stabilizing/destabilizing the vehicle\u0000 following a TBO.","PeriodicalId":42978,"journal":{"name":"SAE International Journal of Vehicle Dynamics Stability and NVH","volume":"5 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87942820","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}
A precise knowledge of the road profile ahead of the vehicle is required to successfully engage a proactive suspension control system. If this profile information is generated by preceding vehicles and stored on a server, the challenge that arises is to accurately determine one’s own position on the server profile. This article presents a localization method based on a particle filter that uses the profile observed by the vehicle to generate an estimated longitudinal position relative to the reference profile on the server. We tested the proposed algorithm on a quarter vehicle test rig using real sensor data and different road profiles originating from various types of roads. In these tests, a mean absolute position error of around 1 cm could be achieved. In addition, the algorithm proved to be robust against local disturbances, added noise, and inaccurate vehicle speed measurements. We also compared the particle filter with a correlation-based method and found it to be advantageous. Even though the intended application lies in the context of proactive suspension control, other use cases with precise localization requirements such as self-driving cars might also benefit from our method.
{"title":"Concept, Implementation, and Performance Comparison of a Particle\u0000 Filter for Accurate Vehicle Localization Using Road Profile Data","authors":"Felix Anhalt, Simon Hafner","doi":"10.4271/10-07-03-0025","DOIUrl":"https://doi.org/10.4271/10-07-03-0025","url":null,"abstract":"A precise knowledge of the road profile ahead of the vehicle is required to\u0000 successfully engage a proactive suspension control system. If this profile\u0000 information is generated by preceding vehicles and stored on a server, the\u0000 challenge that arises is to accurately determine one’s own position on the\u0000 server profile. This article presents a localization method based on a particle\u0000 filter that uses the profile observed by the vehicle to generate an estimated\u0000 longitudinal position relative to the reference profile on the server. We tested\u0000 the proposed algorithm on a quarter vehicle test rig using real sensor data and\u0000 different road profiles originating from various types of roads. In these tests,\u0000 a mean absolute position error of around 1 cm could be achieved. In addition,\u0000 the algorithm proved to be robust against local disturbances, added noise, and\u0000 inaccurate vehicle speed measurements. We also compared the particle filter with\u0000 a correlation-based method and found it to be advantageous. Even though the\u0000 intended application lies in the context of proactive suspension control, other\u0000 use cases with precise localization requirements such as self-driving cars might\u0000 also benefit from our method.","PeriodicalId":42978,"journal":{"name":"SAE International Journal of Vehicle Dynamics Stability and NVH","volume":"24 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77563588","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}
The electrically interconnected suspension (EIS) is a novel suspension system that has gained attention due to its potential to improve vehicle vibration control. This article provides a comprehensive review of EIS and related technologies. It starts with an overview of the research on hydraulic interconnected suspension (HIS) and its limitations. Then, it discusses the development of the electromagnetic suspension (EMS) and its advantages in adjusting mechanical characteristics. The article focuses on the electrical network and decoupling control characteristics of EIS, demonstrating the principle of synchronous decoupling control of multiple vibration modes. A comparison of the structure and control characteristics of EIS and HIS highlights the advantages of EIS in vehicle vibration control. The article concludes by identifying some unresolved issues and potential research areas to guide future studies on EIS, such as improving the controllability and energy efficiency of EIS systems.
{"title":"Electrically Interconnected Suspension and Related Technologies: A\u0000 Comprehensive Review","authors":"H. Du, Pengfei Liu, D. Ning, Nong Zhang","doi":"10.4271/10-07-03-0024","DOIUrl":"https://doi.org/10.4271/10-07-03-0024","url":null,"abstract":"The electrically interconnected suspension (EIS) is a novel suspension system\u0000 that has gained attention due to its potential to improve vehicle vibration\u0000 control. This article provides a comprehensive review of EIS and related\u0000 technologies. It starts with an overview of the research on hydraulic\u0000 interconnected suspension (HIS) and its limitations. Then, it discusses the\u0000 development of the electromagnetic suspension (EMS) and its advantages in\u0000 adjusting mechanical characteristics. The article focuses on the electrical\u0000 network and decoupling control characteristics of EIS, demonstrating the\u0000 principle of synchronous decoupling control of multiple vibration modes. A\u0000 comparison of the structure and control characteristics of EIS and HIS\u0000 highlights the advantages of EIS in vehicle vibration control. The article\u0000 concludes by identifying some unresolved issues and potential research areas to\u0000 guide future studies on EIS, such as improving the controllability and energy\u0000 efficiency of EIS systems.","PeriodicalId":42978,"journal":{"name":"SAE International Journal of Vehicle Dynamics Stability and NVH","volume":"57 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90583244","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}
The tailpipe zero-emission legislation has pushed the automotive industry toward more electrification. Regenerative braking is the capability of electric machines to provide brake torque. So far, the regenerative braking feature is primarily considered due to its effect on energy efficiency. However, using individual e-machines for each wheel makes it possible to apply the antilock braking function due to the fast torque-tracking characteristics of permanent magnet synchronous motors (PMSM). Due to its considerable cost reduction, in this article, a feasibility study is carried out to investigate if the ABS function can be done purely through regenerative braking using a mid-fidelity model-based approach. An uni-tire model of the vehicle with a surface-mount PMSM (SPMSM) model is used to verify the idea. The proposed ABS control system has a hierarchical structure containing a high-level longitudinal slip controller and a low-level SPMSM torque controller. Given the uncertainties of the tire–road dynamics, a sliding mode control method is designed and employed as a high-level slip controller. Also, a PID vector control method is used to keep the SPMSM braking torque at the optimal value requested by the high-level controller. Moreover, in order to estimate the tire longitudinal slip and vehicle velocity, an extended Kalman filter (EKF) is developed that estimates both parameters at the same time. The results show that the proposed hierarchical control and estimators can keep the tire longitudinal slip at the optimal value and prevent the wheel from locking in a variety of road conditions.
{"title":"A Mid-fidelity Model in the Loop Feasibility Study for Implementation\u0000 of Regenerative Antilock Braking System in Electric Vehicles","authors":"Nastaran Ghanami, Kamyar Nikzadfar, Hamidreza Mohammadi Daniali","doi":"10.4271/10-07-03-0022","DOIUrl":"https://doi.org/10.4271/10-07-03-0022","url":null,"abstract":"The tailpipe zero-emission legislation has pushed the automotive industry toward\u0000 more electrification. Regenerative braking is the capability of electric\u0000 machines to provide brake torque. So far, the regenerative braking feature is\u0000 primarily considered due to its effect on energy efficiency. However, using\u0000 individual e-machines for each wheel makes it possible to apply the antilock\u0000 braking function due to the fast torque-tracking characteristics of permanent\u0000 magnet synchronous motors (PMSM). Due to its considerable cost reduction, in\u0000 this article, a feasibility study is carried out to investigate if the ABS\u0000 function can be done purely through regenerative braking using a mid-fidelity\u0000 model-based approach. An uni-tire model of the vehicle with a surface-mount PMSM\u0000 (SPMSM) model is used to verify the idea. The proposed ABS control system has a\u0000 hierarchical structure containing a high-level longitudinal slip controller and\u0000 a low-level SPMSM torque controller. Given the uncertainties of the tire–road\u0000 dynamics, a sliding mode control method is designed and employed as a high-level\u0000 slip controller. Also, a PID vector control method is used to keep the SPMSM\u0000 braking torque at the optimal value requested by the high-level controller.\u0000 Moreover, in order to estimate the tire longitudinal slip and vehicle velocity,\u0000 an extended Kalman filter (EKF) is developed that estimates both parameters at\u0000 the same time. The results show that the proposed hierarchical control and\u0000 estimators can keep the tire longitudinal slip at the optimal value and prevent\u0000 the wheel from locking in a variety of road conditions.","PeriodicalId":42978,"journal":{"name":"SAE International Journal of Vehicle Dynamics Stability and NVH","volume":"17 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77237425","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}
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