Pub Date : 2024-07-30DOI: 10.1177/09544070241265398
Ahmet Emre Cetin, Erhan Akdogan, Suden Battal, Ceyhun Ibolar
The detection of driver distractions is exceptionally important for driving safety. Driver distraction can originate from various sources such as external tasks (e.g., texting or eating) or mental states (e.g., sleepiness, tiredness, anger, and tension). To detect these conditions, most of the previous studies were based on vision-based techniques. These techniques are affected by environmental factors (e.g., day, night, and facial accessories such as glasses and hats). However, the steering wheel is an interface that provides a direct relationship between the driver and vehicle. The driver’s interaction can effectively reflect this behavior and mental state. This study introduced a new method for detecting driver distractions by utilizing force/torque (F/T) sensor data extracted from the steering wheel. An experimental setup was designed and developed to measure the accuracy of the proposed method. To validate the strategy, a machine learning-based algorithm was developed. It demonstrated remarkable performance in determining the position of the driver’s hand on the steering wheel and in inferring with high precision the hand the driver uses to operate the vehicle. The method produced accurate results in all the grip ranges that could be held by the driver within the range of 0°–360°. The support vector machine (SVM) method was used in machine learning. It predicted with a 91.1% accuracy rate.
{"title":"Machine learning-based real time identification of driver posture during driving","authors":"Ahmet Emre Cetin, Erhan Akdogan, Suden Battal, Ceyhun Ibolar","doi":"10.1177/09544070241265398","DOIUrl":"https://doi.org/10.1177/09544070241265398","url":null,"abstract":"The detection of driver distractions is exceptionally important for driving safety. Driver distraction can originate from various sources such as external tasks (e.g., texting or eating) or mental states (e.g., sleepiness, tiredness, anger, and tension). To detect these conditions, most of the previous studies were based on vision-based techniques. These techniques are affected by environmental factors (e.g., day, night, and facial accessories such as glasses and hats). However, the steering wheel is an interface that provides a direct relationship between the driver and vehicle. The driver’s interaction can effectively reflect this behavior and mental state. This study introduced a new method for detecting driver distractions by utilizing force/torque (F/T) sensor data extracted from the steering wheel. An experimental setup was designed and developed to measure the accuracy of the proposed method. To validate the strategy, a machine learning-based algorithm was developed. It demonstrated remarkable performance in determining the position of the driver’s hand on the steering wheel and in inferring with high precision the hand the driver uses to operate the vehicle. The method produced accurate results in all the grip ranges that could be held by the driver within the range of 0°–360°. The support vector machine (SVM) method was used in machine learning. It predicted with a 91.1% accuracy rate.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141872770","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 : 2024-07-26DOI: 10.1177/09544070241264850
Zhaowen Deng, Youqun Zhao, Wei Gao, Qiang Yi, Baohua Wang
At present, the research on improving vehicle handling stability, ride comfort, and driving safety mainly focuses on chassis system control, and rarely considers vehicle active aerodynamic control based on aerodynamic characteristics. Therefore, this paper takes the high-speed vehicle with adjustable tail as the research object, and the integrated stability control of active aerodynamics and active rear-wheel steering has been proposed. First, a linear two-degree-of-freedom (2-DOF) vehicle dynamic reference model was established, and the linear quadratic regulator (LQR) active rear-wheel steering controller was designed. Second, the principle of angle of attack distribution for active aerodynamic system was developed, an active aerodynamic Sliding Mode control (SMC) system was designed, which can automatically adjust the angle of attack of the rear wing, according to the vehicle status. Finally, the integrated stability control of active aerodynamics and active rear-wheel steering was realized. In the CarSim and Matlab/Simulink environment, the response characteristics of the integrated control to vehicle handling stability and safety were analyzed. The results show that the integrated stability control can effectively enhance the handling stability, ride comfort, safety, and road tracking ability of the high-speed vehicle, thus reducing the occurrence of vehicle runaway, rollover, and other dangerous situations.
{"title":"Integrated stability control of active aerodynamics and active rear-wheel steering for high-speed vehicle","authors":"Zhaowen Deng, Youqun Zhao, Wei Gao, Qiang Yi, Baohua Wang","doi":"10.1177/09544070241264850","DOIUrl":"https://doi.org/10.1177/09544070241264850","url":null,"abstract":"At present, the research on improving vehicle handling stability, ride comfort, and driving safety mainly focuses on chassis system control, and rarely considers vehicle active aerodynamic control based on aerodynamic characteristics. Therefore, this paper takes the high-speed vehicle with adjustable tail as the research object, and the integrated stability control of active aerodynamics and active rear-wheel steering has been proposed. First, a linear two-degree-of-freedom (2-DOF) vehicle dynamic reference model was established, and the linear quadratic regulator (LQR) active rear-wheel steering controller was designed. Second, the principle of angle of attack distribution for active aerodynamic system was developed, an active aerodynamic Sliding Mode control (SMC) system was designed, which can automatically adjust the angle of attack of the rear wing, according to the vehicle status. Finally, the integrated stability control of active aerodynamics and active rear-wheel steering was realized. In the CarSim and Matlab/Simulink environment, the response characteristics of the integrated control to vehicle handling stability and safety were analyzed. The results show that the integrated stability control can effectively enhance the handling stability, ride comfort, safety, and road tracking ability of the high-speed vehicle, thus reducing the occurrence of vehicle runaway, rollover, and other dangerous situations.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141786237","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 : 2024-07-26DOI: 10.1177/09544070241262352
Dariusz Szwedowicz, Miguel Alberto Domínguez-Gurría, Demetrio Pérez-Vigueras, Víctor I Rodríguez-Reyes
In this work the parametric evaluation of the influence of the dimensional variation of the arc height of a leaf spring on the energy dissipation and deformation energy is presented. With the use of the finite element package Abaqus, the cyclic force-displacement curve of the leaf spring under a compression test was numerically obtained through a discrete model for four cases, by varying the arc height of the spring, subsequently the energy dissipation and the potential energy was calculated. The discrete model was experimentally validated by performing compression tests on a commercial spring. The obtained results show that varying the arc height influences the amount of energy dissipation and potential energy. It was observed that by decreasing the arc height by 33%, the energy dissipation increased by 50% and the potential energy by 3%, resulting in an increment in the specific damping capacity of 47% with respect to the original model. From the discrete model, it is concluded that the contact pressure, contact area, and slip zones are more uniformly distributed when the arc height is reduced by 33%, besides of a decrease in the mass of the spring, results which may be useful for car suspension designers.
{"title":"Numerical case study of the influence of dimensional variation of a semi-elliptic spring on the passive energy dissipation","authors":"Dariusz Szwedowicz, Miguel Alberto Domínguez-Gurría, Demetrio Pérez-Vigueras, Víctor I Rodríguez-Reyes","doi":"10.1177/09544070241262352","DOIUrl":"https://doi.org/10.1177/09544070241262352","url":null,"abstract":"In this work the parametric evaluation of the influence of the dimensional variation of the arc height of a leaf spring on the energy dissipation and deformation energy is presented. With the use of the finite element package Abaqus, the cyclic force-displacement curve of the leaf spring under a compression test was numerically obtained through a discrete model for four cases, by varying the arc height of the spring, subsequently the energy dissipation and the potential energy was calculated. The discrete model was experimentally validated by performing compression tests on a commercial spring. The obtained results show that varying the arc height influences the amount of energy dissipation and potential energy. It was observed that by decreasing the arc height by 33%, the energy dissipation increased by 50% and the potential energy by 3%, resulting in an increment in the specific damping capacity of 47% with respect to the original model. From the discrete model, it is concluded that the contact pressure, contact area, and slip zones are more uniformly distributed when the arc height is reduced by 33%, besides of a decrease in the mass of the spring, results which may be useful for car suspension designers.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141786058","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}
Human-machine conflict has a significant impact on driving safety, posing a vital challenge in the design of lane departure prevention (LDP) systems. To address the issue, this paper proposes a driver-intelligent vehicle cooperative steering torque assistance control strategy. The lane departure decision-making module based on the gated recurrent unit (GRU) is used to predict the lateral deviation of the vehicle and to make real-time decisions regarding the switching of the model predictive control (MPC) based assistance controller. Next, the conflict performance between the MPC lane keeping and conflict reduction (MPC-LKCR) controller’s torque and the driver’s torque is added to the optimization objective of the MPC lane keeping (MPC-LK) controller, while the lane keeping performance is continually retained. That is because a shared factor based on the fuzzy model is designed with the ability to adjust the assistance torque within the MPC-LKCR controller according to the driver’s intention. Finally, after the overall optimization of the MPC-LKCR controller, the final torque after the superposition of driver and assistance torque acts on the steering column to realize the human-machine cooperative steering control. The driving data from 52 drivers were collected to train the GRU model offline. The proposed strategy was simulated and analyzed under different driving scenarios, and hardware-in-the-loop experiments were completed on a driving simulator to validate it. Hardware-in-the-loop results show that the average conflict intensity and conflict time ratio are reduced by 23.8% and 34.4% under the MPC-LKCR controller compared to the MPC-LK controller. The strategy not only accomplishes the task of vehicle lane departure but also effectively reduces the time and intensity of human-machine conflicts.
{"title":"Cooperative control for lane departure prevention based on model predictive control and gated recurrent unit model","authors":"Zengke Qin, Lie Guo, Jian Wu, Pingshu Ge, Xin Liu, Liyuan Zhao","doi":"10.1177/09544070241264589","DOIUrl":"https://doi.org/10.1177/09544070241264589","url":null,"abstract":"Human-machine conflict has a significant impact on driving safety, posing a vital challenge in the design of lane departure prevention (LDP) systems. To address the issue, this paper proposes a driver-intelligent vehicle cooperative steering torque assistance control strategy. The lane departure decision-making module based on the gated recurrent unit (GRU) is used to predict the lateral deviation of the vehicle and to make real-time decisions regarding the switching of the model predictive control (MPC) based assistance controller. Next, the conflict performance between the MPC lane keeping and conflict reduction (MPC-LKCR) controller’s torque and the driver’s torque is added to the optimization objective of the MPC lane keeping (MPC-LK) controller, while the lane keeping performance is continually retained. That is because a shared factor based on the fuzzy model is designed with the ability to adjust the assistance torque within the MPC-LKCR controller according to the driver’s intention. Finally, after the overall optimization of the MPC-LKCR controller, the final torque after the superposition of driver and assistance torque acts on the steering column to realize the human-machine cooperative steering control. The driving data from 52 drivers were collected to train the GRU model offline. The proposed strategy was simulated and analyzed under different driving scenarios, and hardware-in-the-loop experiments were completed on a driving simulator to validate it. Hardware-in-the-loop results show that the average conflict intensity and conflict time ratio are reduced by 23.8% and 34.4% under the MPC-LKCR controller compared to the MPC-LK controller. The strategy not only accomplishes the task of vehicle lane departure but also effectively reduces the time and intensity of human-machine conflicts.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141784342","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 : 2024-07-26DOI: 10.1177/09544070241262353
Zhifei Zhang, Wencheng Yang, Sishi Cao, Xuhui Luo
Acoustic packages are commonly used to reduce the mid-high frequency noise in the automobile, but fully characterizing their absorption and insulation mechanisms poses challenges. Introducing a data-driven approach to analyze their performance, existing research lacks clarity on the factors influencing acoustic package efficacy when constructing approximate models. To alleviate this, a method of optimizing the acoustic package by combining range analysis with a Response Surface Methodology (RSM) model is proposed in this paper. Initially, a validated Statistical Energy Analysis (SEA) model predicts automobile interior noise, pinpointing the dash panel as a key component for optimization through contribution analysis. Then, acoustic material tests are conducted to design the acoustic package. To compare the design scheme and the original scheme for the acoustic package in the automobile, the simulation and the test of the automobile ATF are performed and the automobile SEA model is verified through the test. Based on the range analysis, an RSM model is developed with the significant factors as input and the sound pressure level (SPL) of the driver’s head acoustic cavity as output. Genetic algorithm optimization is finally performed to obtain the optimized scheme within constrained thickness and weight. The results reveal that the acoustic package optimized scheme effectively improves the noise reduction effect in the mid-frequency range and decreases the weight of the acoustic package, which promotes the comprehensive performance of the acoustic package.
{"title":"Design and optimization of acoustic packages using RSM coupled with range analysis","authors":"Zhifei Zhang, Wencheng Yang, Sishi Cao, Xuhui Luo","doi":"10.1177/09544070241262353","DOIUrl":"https://doi.org/10.1177/09544070241262353","url":null,"abstract":"Acoustic packages are commonly used to reduce the mid-high frequency noise in the automobile, but fully characterizing their absorption and insulation mechanisms poses challenges. Introducing a data-driven approach to analyze their performance, existing research lacks clarity on the factors influencing acoustic package efficacy when constructing approximate models. To alleviate this, a method of optimizing the acoustic package by combining range analysis with a Response Surface Methodology (RSM) model is proposed in this paper. Initially, a validated Statistical Energy Analysis (SEA) model predicts automobile interior noise, pinpointing the dash panel as a key component for optimization through contribution analysis. Then, acoustic material tests are conducted to design the acoustic package. To compare the design scheme and the original scheme for the acoustic package in the automobile, the simulation and the test of the automobile ATF are performed and the automobile SEA model is verified through the test. Based on the range analysis, an RSM model is developed with the significant factors as input and the sound pressure level (SPL) of the driver’s head acoustic cavity as output. Genetic algorithm optimization is finally performed to obtain the optimized scheme within constrained thickness and weight. The results reveal that the acoustic package optimized scheme effectively improves the noise reduction effect in the mid-frequency range and decreases the weight of the acoustic package, which promotes the comprehensive performance of the acoustic package.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141784394","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 : 2024-07-26DOI: 10.1177/09544070241265161
Heng Du, Hanjin Li, Kaiyi Ding, Su Li, Jianchao Yu
Steering system of heavy vehicle facing intelligent and green development needs to satisfy the requirements of high precision and energy-efficient dynamic steering. Traditional steering systems use valved servo systems, which offer high steering accuracy but result in significant energy dissipation at the valve ports. In contrast, the variable speed pump control system (VSPCS) realizes the precise servo of steering system through direct volume control, which basically eliminates the energy dissipation at the valve port. However, the VSPCS lacks sufficient system stiffness due to low back pressure, making it difficult to achieve precise steering. To address these limitations, this paper proposes a back pressure controllable variable speed pump controlled steering system scheme (BCVSPCSS), which combines the energy-efficient flow supply of the VSPCS with a servo-proportional valve is used for back pressure control to, improving the dynamic performance of the system. This integration allows for precise steering while maintaining energy efficiency; The design of a dual objective nonlinear control strategy for angle and back pressure is crucial to deal with uncertainty and nonlinearity in the system. The Lyapunov analysis shows that the closed-loop system has asymptotic stability. In this paper, the experimental bench of BCVSPCSS is built for experimental verification. The results show that back pressure control effectively enhances the system’s immunity. Under the same working conditions, the maximum angle error of the two systems is roughly the same, both around 1°, while the energy consumption of BCVSPCSS is reduced by about 84.6% compared to the valve controlled steering system.
{"title":"Research on energy saving and control characteristics of back pressure controllable variable speed pump controlled steering system for heavy vehicles","authors":"Heng Du, Hanjin Li, Kaiyi Ding, Su Li, Jianchao Yu","doi":"10.1177/09544070241265161","DOIUrl":"https://doi.org/10.1177/09544070241265161","url":null,"abstract":"Steering system of heavy vehicle facing intelligent and green development needs to satisfy the requirements of high precision and energy-efficient dynamic steering. Traditional steering systems use valved servo systems, which offer high steering accuracy but result in significant energy dissipation at the valve ports. In contrast, the variable speed pump control system (VSPCS) realizes the precise servo of steering system through direct volume control, which basically eliminates the energy dissipation at the valve port. However, the VSPCS lacks sufficient system stiffness due to low back pressure, making it difficult to achieve precise steering. To address these limitations, this paper proposes a back pressure controllable variable speed pump controlled steering system scheme (BCVSPCSS), which combines the energy-efficient flow supply of the VSPCS with a servo-proportional valve is used for back pressure control to, improving the dynamic performance of the system. This integration allows for precise steering while maintaining energy efficiency; The design of a dual objective nonlinear control strategy for angle and back pressure is crucial to deal with uncertainty and nonlinearity in the system. The Lyapunov analysis shows that the closed-loop system has asymptotic stability. In this paper, the experimental bench of BCVSPCSS is built for experimental verification. The results show that back pressure control effectively enhances the system’s immunity. Under the same working conditions, the maximum angle error of the two systems is roughly the same, both around 1°, while the energy consumption of BCVSPCSS is reduced by about 84.6% compared to the valve controlled steering system.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141784395","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 : 2024-07-26DOI: 10.1177/09544070241265631
Weihe Liang, Shenhao Zhang, Wanzhong Zhao, Chunyan Wang, Zhongkai Luan, Min Wang
The dual-winding steer-by-wire (DW-SBW) system is a novel steer-by-wire system with dual-winding permanent magnet synchronous motors, which improves steering capability and safety. However, the current imbalance in two stator windings may lead to increased current harmonic and torque ripple, resulting in steering performance degradation and safety jeopardization. Therefore, in order to improve the current balancing capability of the DW-SBW system, this paper proposes a cross-coupling active current balance control strategy. The dynamic model and the current imbalance model of the DW-SBW system are established. The mathematical relationship between the winding parameters asymmetry and current imbalance is derived, and the impact of current imbalance on current harmonic and steering performance is revealed. A radial basis function (RBF) based active current balance fast terminal sliding mode control (FTSMC) strategy for a DW-SBW system is proposed. The fast terminal sliding mode control is applied to cross-compensate the q-axis current loop control output of the two stator windings, while the RBF neural network is used to estimate the asymmetry of the resistance and inductance parameters of the two windings. The performance of the proposed FTSMC-RBF controller is validated through computer simulations and dual-winding motor experiments. The results demonstrate that the proposed FTSMC-RBF controller is more robust and provides better current balancing performance than the FTSMC in the presence of model parameter uncertainties.
{"title":"Cross-coupling active current balance fast terminal sliding mode control for dual-winding steer-by-wire system","authors":"Weihe Liang, Shenhao Zhang, Wanzhong Zhao, Chunyan Wang, Zhongkai Luan, Min Wang","doi":"10.1177/09544070241265631","DOIUrl":"https://doi.org/10.1177/09544070241265631","url":null,"abstract":"The dual-winding steer-by-wire (DW-SBW) system is a novel steer-by-wire system with dual-winding permanent magnet synchronous motors, which improves steering capability and safety. However, the current imbalance in two stator windings may lead to increased current harmonic and torque ripple, resulting in steering performance degradation and safety jeopardization. Therefore, in order to improve the current balancing capability of the DW-SBW system, this paper proposes a cross-coupling active current balance control strategy. The dynamic model and the current imbalance model of the DW-SBW system are established. The mathematical relationship between the winding parameters asymmetry and current imbalance is derived, and the impact of current imbalance on current harmonic and steering performance is revealed. A radial basis function (RBF) based active current balance fast terminal sliding mode control (FTSMC) strategy for a DW-SBW system is proposed. The fast terminal sliding mode control is applied to cross-compensate the q-axis current loop control output of the two stator windings, while the RBF neural network is used to estimate the asymmetry of the resistance and inductance parameters of the two windings. The performance of the proposed FTSMC-RBF controller is validated through computer simulations and dual-winding motor experiments. The results demonstrate that the proposed FTSMC-RBF controller is more robust and provides better current balancing performance than the FTSMC in the presence of model parameter uncertainties.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141786059","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 : 2024-07-26DOI: 10.1177/09544070241265984
Sen Zhan, Yu Huang, Fei Li, Yanli Yin, Chunsheng Liu
In low-temperature conditions, a reasonable control strategy for thermal management systems can effectively alleviate range anxiety in pure electric vehicles and improve their adaptability to various working conditions. To further enhance the adaptability of thermal management system control strategies in different working conditions, this paper proposes a multi-objective control strategy based on Q-learning algorithm. Firstly, a pure electric vehicle model based on power-thermal coupling is established. The accuracy of the model is validated by comparing the simulation results from combined Amesim and Matlab/Simulink simulations with experimental data. Secondly, taking into consideration the factors such as vehicle economy, powertrain performance, and cabin comfort, a novel control strategy utilizing the Q-learning algorithm for the thermal management system of pure electric vehicle is developed. Finally, the efficacy of Q-learning control strategy is analyzed by simulations conducted under NEDC and WLTC conditions, with an initial temperature of −20°C. The results showed that, compared to the rule-based control strategy in WLTC and NEDC working conditions, the comprehensive improvement effect of Q-learning control strategy is 9.35% and 10.76% respectively. Moreover, the Q-learning control strategy achieves 94.25% and 90.19% of the global optimal control effect obtained through DP. The results indicate that the proposed control strategy has good adaptability to different working conditions.
{"title":"Research on multi-objective control strategy of thermal management system of pure electric vehicle at low temperature based on Q-learning algorithm","authors":"Sen Zhan, Yu Huang, Fei Li, Yanli Yin, Chunsheng Liu","doi":"10.1177/09544070241265984","DOIUrl":"https://doi.org/10.1177/09544070241265984","url":null,"abstract":"In low-temperature conditions, a reasonable control strategy for thermal management systems can effectively alleviate range anxiety in pure electric vehicles and improve their adaptability to various working conditions. To further enhance the adaptability of thermal management system control strategies in different working conditions, this paper proposes a multi-objective control strategy based on Q-learning algorithm. Firstly, a pure electric vehicle model based on power-thermal coupling is established. The accuracy of the model is validated by comparing the simulation results from combined Amesim and Matlab/Simulink simulations with experimental data. Secondly, taking into consideration the factors such as vehicle economy, powertrain performance, and cabin comfort, a novel control strategy utilizing the Q-learning algorithm for the thermal management system of pure electric vehicle is developed. Finally, the efficacy of Q-learning control strategy is analyzed by simulations conducted under NEDC and WLTC conditions, with an initial temperature of −20°C. The results showed that, compared to the rule-based control strategy in WLTC and NEDC working conditions, the comprehensive improvement effect of Q-learning control strategy is 9.35% and 10.76% respectively. Moreover, the Q-learning control strategy achieves 94.25% and 90.19% of the global optimal control effect obtained through DP. The results indicate that the proposed control strategy has good adaptability to different working conditions.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141784392","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}
A novel mechanical-electrical-hydraulic regenerative suspension system (MEH-RSS) suitable for tracked vehicles is proposed to improve the ride comfort of tracked vehicles while efficiently recovering the suspension vibration energy and improving the suspension working reliability. The dynamical model considering the dynamic damping coefficient of the MEH-RSS is established and the ride comfort analysis of tracked vehicle is carried out to verify the vibration reduction performance of the MEH-RSS. A simulated test of the energy recovery module is designed based on the bidirectional energy management control strategy, and the results show that the MEH-RSS can achieve semi-active damping force adjustment function and efficient energy recovery. The simulation results of a single bogie wheel 2-DOF model show that the damping coefficient of the MEH-RSS can adapt to the changes in road excitation characteristics, and semi-active control function can be achieved by adjusting the external resistance. The average energy recovery power of 4442 W can be reached on E-class off-road with a driving velocity of 10 m/s. The half vehicle 8-DOF model simulation results show that under passive working conditions, the root-mean-square (RMS) value of the vertical acceleration of a tracked vehicle equipped with MEH-RSS is reduced by 5.7% relative to that of a tracked vehicle equipped with traditional passive suspension (TPS) on E-class off-road. The MEH-RSS can effectively improve the ride comfort of tracked vehicles while achieving vibration energy recovery.
本文提出了一种适用于履带式车辆的新型机电液再生悬架系统（MEH-RSS），在有效回收悬架振动能量、提高悬架工作可靠性的同时，改善了履带式车辆的乘坐舒适性。建立了考虑 MEH-RSS 动态阻尼系数的动力学模型，并对履带车辆的乘坐舒适性进行了分析，以验证 MEH-RSS 的减振性能。基于双向能量管理控制策略，设计了能量回收模块的仿真试验，结果表明 MEH-RSS 可实现半主动阻尼力调节功能和高效的能量回收。单转向架车轮 2-DOF 模型的仿真结果表明，MEH-RSS 的阻尼系数能够适应路面激励特性的变化，并可通过调节外阻力实现半主动控制功能。在行驶速度为 10 m/s 的 E 级越野路面上，平均能量回收功率可达 4442 W。半车 8-DOF 模型模拟结果表明，在被动工况下，配备 MEH-RSS 的履带式车辆在 E 级越野路面上的垂直加速度均方根值比配备传统被动悬架（TPS）的履带式车辆降低了 5.7%。MEH-RSS 可有效改善履带式车辆的乘坐舒适性，同时实现振动能量回收。
{"title":"Energy recovery and ride comfort analysis of mechanical-electrical-hydraulic regenerative suspension system for tracked vehicle","authors":"Weijie Zhang, Yong Guo, Guosheng Wang, Qihui Ling, Zhewu Chen","doi":"10.1177/09544070241265034","DOIUrl":"https://doi.org/10.1177/09544070241265034","url":null,"abstract":"A novel mechanical-electrical-hydraulic regenerative suspension system (MEH-RSS) suitable for tracked vehicles is proposed to improve the ride comfort of tracked vehicles while efficiently recovering the suspension vibration energy and improving the suspension working reliability. The dynamical model considering the dynamic damping coefficient of the MEH-RSS is established and the ride comfort analysis of tracked vehicle is carried out to verify the vibration reduction performance of the MEH-RSS. A simulated test of the energy recovery module is designed based on the bidirectional energy management control strategy, and the results show that the MEH-RSS can achieve semi-active damping force adjustment function and efficient energy recovery. The simulation results of a single bogie wheel 2-DOF model show that the damping coefficient of the MEH-RSS can adapt to the changes in road excitation characteristics, and semi-active control function can be achieved by adjusting the external resistance. The average energy recovery power of 4442 W can be reached on E-class off-road with a driving velocity of 10 m/s. The half vehicle 8-DOF model simulation results show that under passive working conditions, the root-mean-square (RMS) value of the vertical acceleration of a tracked vehicle equipped with MEH-RSS is reduced by 5.7% relative to that of a tracked vehicle equipped with traditional passive suspension (TPS) on E-class off-road. The MEH-RSS can effectively improve the ride comfort of tracked vehicles while achieving vibration energy recovery.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141784393","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}
In this paper, stabilization of tele-driving system in presence of communication time delay is studied using a 103 DOF vehicle model generated in ADAMS/Car Software. The purpose of this study is achieving a real sense of driving for tele-driving system in virtual environment under complicated driving and road conditions. To this aim, the performance of the various control architectures, in terms of position and force tracking, are investigated. Hence, the two-channel architecture is chosen as the most appropriate scheme to implement the haptic control system for the vehicle steering mechanism. In this paper, we designed an effective haptic feedback control for vehicle steering mechanism in the tele-driving system so that a command can be exerted to steering wheel by the human operator, which passes through the communication channels and will be applied to unmanned vehicle steering system. It is verified that an appropriate coordination performance under the human input can be obtained with the proposed control framework. To overcome the possible instability problem associated with existence of time-delay in communication channels, wave variables and their corrections are effectively embedded into the control system. Finally, the proposed bilateral tele-driving control on a rough 3D road surface at complicated driving and road conditions in the presence of time-delay are examined comprehensively.
{"title":"Haptic tele-driving design of vehicle steering control system with communication delay under complicated driving and road conditions","authors":"Mohammadreza Sajjadi, Mahmood Chahari, Hassan Salarieh","doi":"10.1177/09544070241261111","DOIUrl":"https://doi.org/10.1177/09544070241261111","url":null,"abstract":"In this paper, stabilization of tele-driving system in presence of communication time delay is studied using a 103 DOF vehicle model generated in ADAMS/Car Software. The purpose of this study is achieving a real sense of driving for tele-driving system in virtual environment under complicated driving and road conditions. To this aim, the performance of the various control architectures, in terms of position and force tracking, are investigated. Hence, the two-channel architecture is chosen as the most appropriate scheme to implement the haptic control system for the vehicle steering mechanism. In this paper, we designed an effective haptic feedback control for vehicle steering mechanism in the tele-driving system so that a command can be exerted to steering wheel by the human operator, which passes through the communication channels and will be applied to unmanned vehicle steering system. It is verified that an appropriate coordination performance under the human input can be obtained with the proposed control framework. To overcome the possible instability problem associated with existence of time-delay in communication channels, wave variables and their corrections are effectively embedded into the control system. Finally, the proposed bilateral tele-driving control on a rough 3D road surface at complicated driving and road conditions in the presence of time-delay are examined comprehensively.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141784396","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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