The reduction of fuel consumption in engines is always considered of vital importance.Along these lines,in this work,this goal was attained by optimizing the heavy-duty commercial vehicle engine control strategy.More ...The reduction of fuel consumption in engines is always considered of vital importance.Along these lines,in this work,this goal was attained by optimizing the heavy-duty commercial vehicle engine control strategy.More specifically,at first,a general first principles model for heavy-duty commercial vehicles and a transient fuel consumptionmodel for heavy-duty commercial vehicles were developed and the parameters were adjusted to fit the empirical data.The accuracy of the proposed modelwas demonstrated fromthe stage and the final results.Next,the control optimization problem resulting in low fuel consumption in heavy commercial vehicles was described,with minimal fuel usage as the optimization goal and throttle opening as the control variable.Then,a time-continuous engine management approach was assessed.Next,the factors that influence low fuel consumption in heavy-duty commercial vehicles were systematically examined.To reduce the computing complexity,the control strategies related to the time constraints of the engine were parametrized using three different methods.The most effective solution was obtained by applying a global optimization strategy because the constrained optimization problem was nonlinear.Finally,the effectiveness of the low-fuel consumption engine control strategy was demonstrated by comparing the simulated and field test results.展开更多
Regarding the lane keeping system,path tracking accuracy and lateral stability at high speeds need to be taken into account especially for commercial vehicles due to the characteristics of larger mass,longer wheelbase...Regarding the lane keeping system,path tracking accuracy and lateral stability at high speeds need to be taken into account especially for commercial vehicles due to the characteristics of larger mass,longer wheelbase and higher mass center.To improve the performance mentioned above comprehensively,the control strategy based on improved artificial potential field(APF)algorithm is proposed.In the paper,time to lane crossing(TLC)is introduced into the potential field function to enhance the accuracy of path tracking,meanwhile the vehicle dynamics parameters including yaw rate and lateral acceleration are chosen as the repulsive force field source.The lane keeping controller based on improved APF algorithm is designed and the stability of the control system is proved based on Lyapunov theory.In addition,adaptive inertial weight particle swarm optimization algorithm(AIWPSO)is applied to optimize the gain of each potential field function.The co-simulation results indicate that the comprehensive evaluation index respecting lane tracking accuracy and lateral stability is reduced remarkably.Finally,the proposed control strategy is verified by the HiL test.It provides a beneficial reference for dynamics control of commercial vehicles and enriches the theoretical development and practical application of artificial potential field method in the field of intelligent driving.展开更多
Fire incidents in commercial vehicles pose significant risks to passengers, drivers, and cargo. Traditional fire extinguishing systems, while effective, may have limitations in terms of response time, coverage, and hu...Fire incidents in commercial vehicles pose significant risks to passengers, drivers, and cargo. Traditional fire extinguishing systems, while effective, may have limitations in terms of response time, coverage, and human intervention [1]. This study investigates the efficacy of a novel fire suppression technology—the Exploding Fire Extinguishing Ball (EFEB) —as an alternative and complementary fire safety solution for commercial vehicles. The research employs a multidisciplinary approach, encompassing engineering, materials science, fire safety, and human factors analysis. A systematic literature review establishes a comprehensive understanding of existing fire suppression technologies, including EFEBs. Subsequently, this study analyzes the unique features of EFEBs, such as automatic activation, as well as manual activation upon exposure to fire, and their potential to provide rapid, localized, and autonomous fire suppression. The study presents original experimental investigations to assess the performance and effectiveness of EFEBs in various fire scenarios representative of commercial vehicles. Experiments include controlled fires in confined spaces and dynamic simulations to emulate real-world fire incidents. Data on activation times, extinguishing capability, and coverage area are collected and analyzed to compare the efficacy of EFEBs with traditional fire extinguishing methods. Furthermore, this research shows the practical aspects of implementing EFEBs in commercial vehicles. A feasibility study examines the integration challenges, cost-benefit analysis, and potential regulatory implications. The study also addresses the impact of EFEBs on vehicle weight, stability, and overall safety. Human factors and user acceptance are crucial elements in adopting new safety technologies. Therefore, this research utilizes an experimental design to assess the performance and effectiveness of EFEBs in various fire scenarios representative of commercial vehicles. This dissertation presents original controlled experiments to emulate real-world fire incidents, including controlled fires in confined spaces and dynamic simulations. The experimental approach ensures rigorous evaluation and objective insights into EFEBs’ potential as an autonomous fire suppression system for commercial vehicles. This includes the perspectives of drivers, passengers, fleet operators, insurance agencies, and regulatory bodies. Factors influencing trust, perceived safety, and willingness to adopt EFEBs are analyzed to provide insights into the successful integration of this technology. The findings of this research will contribute to the knowledge of fire safety technology and expand the understanding of the applicability of EFEBs in commercial vehicles.展开更多
The extended Kalman filter (EKF) algorithm and acceleration sensor measurements were used to identify vehiclemass and road gradient in the work. Four different states of fixed mass, variable mass, fixed slope and vari...The extended Kalman filter (EKF) algorithm and acceleration sensor measurements were used to identify vehiclemass and road gradient in the work. Four different states of fixed mass, variable mass, fixed slope and variableslope were set to simulate real-time working conditions, respectively. A comprehensive electric commercial vehicleshifting strategy was formulated according to the identification results. The co-simulation results showed that,compared with the recursive least square (RLS) algorithm, the proposed algorithm could identify the real-timevehicle mass and road gradient quickly and accurately. The comprehensive shifting strategy formulated had thefollowing advantages, e.g., avoiding frequent shifting of vehicles up the hill, making full use ofmotor braking downthe hill, and improving the overall performance of vehicles.展开更多
When heavy-duty commercial vehicles(HDCVs)must engage in emergency braking,uncertain conditions such as the brake pressure and road profile variations will inevitably affect braking control.To minimize these uncertain...When heavy-duty commercial vehicles(HDCVs)must engage in emergency braking,uncertain conditions such as the brake pressure and road profile variations will inevitably affect braking control.To minimize these uncertainties,we propose a combined longitudinal and lateral controller method based on stochastic model predictive control(SMPC)that is achieved via Chebyshev–Cantelli inequality.In our method,SMPC calculates braking control inputs based on a finite time prediction that is achieved by solving stochastic programming elements,including chance constraints.To accomplish this,SMPC explicitly describes the probabilistic uncertainties to be used when designing a robust control strategy.The main contribution of this paper is the proposal of a braking control formulation that is robust against probabilistic friction circle uncertainty effects.More specifically,the use of Chebyshev–Cantelli inequality suppresses road profile influences,which have characteristics that are different from the Gaussian distribution,thereby improving both braking robustness and control performance against statistical disturbances.Additionally,since the Kalman filtering(KF)algorithm is used to obtain the expectation and covariance used for calculating deterministic transformed chance constraints,the SMPC is reformulated as a KF embedded deterministic MPC.Herein,the effectiveness of our proposed method is verified via a MATLAB/Simulink and TruckSim co-simulation.展开更多
今年IAA的口号“Driven by Ideas'(创意驱动)在这场全球最重要的交通、物流和移动性行业贸易展上真正得到了贯彻落实。在汉诺威,未来正在变成看得见的现实。今年IAA的口号“Driven by Ideas”(创意驱动)在这场全球最重要的交通、物...今年IAA的口号“Driven by Ideas'(创意驱动)在这场全球最重要的交通、物流和移动性行业贸易展上真正得到了贯彻落实。在汉诺威,未来正在变成看得见的现实。今年IAA的口号“Driven by Ideas”(创意驱动)在这场全球最重要的交通、物流和移动性行业贸易展上真正得到了贯彻落实。在汉诺威,未来正在变成看得见的现实。整个商用车行业向IAA观众展示了创新、创造力和先锋精神。这些品质表现在332款产品的全球首发和1 00多款产品的欧洲首发。此次IAA更是决策者的贸易展,并且国际化程度前所未有。展开更多
Obstructive Sleep Apnea (OSA) has been identified by many studies as one of the significant contributing factors for motor vehicle accidents. However, only a small number of studies have been conducted in Malaysia. Ob...Obstructive Sleep Apnea (OSA) has been identified by many studies as one of the significant contributing factors for motor vehicle accidents. However, only a small number of studies have been conducted in Malaysia. Objective: This paper aims to highlight the prevalence of OSA among truck drivers and express bus drivers in Malaysia and efforts being undertaken to address issues related to OSA among commercial vehicle drivers. Methodology: Two separate studies were conducted: a cross sectional study among truck drivers and secondly among express bus drivers. The screening process for identifying the high risk group for OSA was done using Berlin questionnaire. Meanwhile, among express bus drivers, OSA was confirmed with sleep study using polysomnography test. Result: Screening of risk group of OSA among truck drivers revealed that 14.6% (19) of drivers were categorized as having high risk of OSA while 85.4% (111) having low risk of OSA. While, in another study, polysomnography test among express bus drivers showed that 83 (28.7%) had mild OSA, 26 (9.0%) had AHI moderate OSA, and 19 drivers (6.6%) severe OSA. Conclusion: This paper highlighted the issues of OSA among commercial vehicle drivers in Malaysia. With an alarming high prevalence, OSA should be a major road safety concern in this country. A special study focusing on sleep and fatigue related crashes may need to be conducted to complement the current studies and full implementation of existing efforts and initiatives to address OSA in road crashes should be realized by the relevant authorities.展开更多
Latest data from the China Association of Automobile Manufacturers(CAAM) shows that through 2010.China’s automobile sales surpassed 18 million, breaking the world record of annual auto sales previously held by the Un...Latest data from the China Association of Automobile Manufacturers(CAAM) shows that through 2010.China’s automobile sales surpassed 18 million, breaking the world record of annual auto sales previously held by the United States.Now that China has become a major global auto production player, how is Foton faring? CAAM statistics said production and sales volume of展开更多
The heavy-duty vehicle fleet involved in delivering water and sand makes noticeable issues of exhaust emissions and fuel consumption in the process of shale gas development. To examine the possibility of converting th...The heavy-duty vehicle fleet involved in delivering water and sand makes noticeable issues of exhaust emissions and fuel consumption in the process of shale gas development. To examine the possibility of converting these heavy-duty diesel engines to run on natural gas-diesel dual-fuel, a transient engine duty cycle representing the real-world engine working conditions is necessary. In this paper, a methodology is proposed, and a target engine duty cycle comprising of 2231 seconds is developed from on-road data collected from 11 on-road sand and water hauling trucks. The similarity of inherent characteristics of the developed cycle and the base trip observed is evidenced by the 2.05% error of standard deviation and average values for normalized engine speed and engine torque. Our results show that the proposed approach is expected to produce a representative cycle of in-use heavy-duty engine behavior.展开更多
基金This work was supported in part by the Science and Technology Major Project of Guangxi under Grant AA22068001in part by the Key Research and Development Program of Guangxi AB21196029+3 种基金in part by the Project of National Natural Science Foundation of China 51965012in part by the Scientific Research and TechnologyDevelopment in Liuzhou 2022AAA0102,2021AAA0104 and 2021AAA0112in part by Agricultural Science and Technology Innovation and Extension Special Project of Jiangsu Province NJ2021-21,in part by the Guangxi Key Laboratory of Manufacturing System and Advanced Manufacturing Technology,in part by the Guilin University of Electronic Technology 20-065-40-004Zin part by the Innovation Project of GUET Graduate Education 2022YCXS017.
文摘The reduction of fuel consumption in engines is always considered of vital importance.Along these lines,in this work,this goal was attained by optimizing the heavy-duty commercial vehicle engine control strategy.More specifically,at first,a general first principles model for heavy-duty commercial vehicles and a transient fuel consumptionmodel for heavy-duty commercial vehicles were developed and the parameters were adjusted to fit the empirical data.The accuracy of the proposed modelwas demonstrated fromthe stage and the final results.Next,the control optimization problem resulting in low fuel consumption in heavy commercial vehicles was described,with minimal fuel usage as the optimization goal and throttle opening as the control variable.Then,a time-continuous engine management approach was assessed.Next,the factors that influence low fuel consumption in heavy-duty commercial vehicles were systematically examined.To reduce the computing complexity,the control strategies related to the time constraints of the engine were parametrized using three different methods.The most effective solution was obtained by applying a global optimization strategy because the constrained optimization problem was nonlinear.Finally,the effectiveness of the low-fuel consumption engine control strategy was demonstrated by comparing the simulated and field test results.
基金Supported by National Natural Science Foundation of China(Grant Nos.51605199,U20A20333,52225212)Six Talent Peak Funding Projects in Jiangsu Province of China(Grant No.2019-GDZB-084)Key Science and Technology Support Program in Taizhou City of China(Grant No.TG202307).
文摘Regarding the lane keeping system,path tracking accuracy and lateral stability at high speeds need to be taken into account especially for commercial vehicles due to the characteristics of larger mass,longer wheelbase and higher mass center.To improve the performance mentioned above comprehensively,the control strategy based on improved artificial potential field(APF)algorithm is proposed.In the paper,time to lane crossing(TLC)is introduced into the potential field function to enhance the accuracy of path tracking,meanwhile the vehicle dynamics parameters including yaw rate and lateral acceleration are chosen as the repulsive force field source.The lane keeping controller based on improved APF algorithm is designed and the stability of the control system is proved based on Lyapunov theory.In addition,adaptive inertial weight particle swarm optimization algorithm(AIWPSO)is applied to optimize the gain of each potential field function.The co-simulation results indicate that the comprehensive evaluation index respecting lane tracking accuracy and lateral stability is reduced remarkably.Finally,the proposed control strategy is verified by the HiL test.It provides a beneficial reference for dynamics control of commercial vehicles and enriches the theoretical development and practical application of artificial potential field method in the field of intelligent driving.
文摘Fire incidents in commercial vehicles pose significant risks to passengers, drivers, and cargo. Traditional fire extinguishing systems, while effective, may have limitations in terms of response time, coverage, and human intervention [1]. This study investigates the efficacy of a novel fire suppression technology—the Exploding Fire Extinguishing Ball (EFEB) —as an alternative and complementary fire safety solution for commercial vehicles. The research employs a multidisciplinary approach, encompassing engineering, materials science, fire safety, and human factors analysis. A systematic literature review establishes a comprehensive understanding of existing fire suppression technologies, including EFEBs. Subsequently, this study analyzes the unique features of EFEBs, such as automatic activation, as well as manual activation upon exposure to fire, and their potential to provide rapid, localized, and autonomous fire suppression. The study presents original experimental investigations to assess the performance and effectiveness of EFEBs in various fire scenarios representative of commercial vehicles. Experiments include controlled fires in confined spaces and dynamic simulations to emulate real-world fire incidents. Data on activation times, extinguishing capability, and coverage area are collected and analyzed to compare the efficacy of EFEBs with traditional fire extinguishing methods. Furthermore, this research shows the practical aspects of implementing EFEBs in commercial vehicles. A feasibility study examines the integration challenges, cost-benefit analysis, and potential regulatory implications. The study also addresses the impact of EFEBs on vehicle weight, stability, and overall safety. Human factors and user acceptance are crucial elements in adopting new safety technologies. Therefore, this research utilizes an experimental design to assess the performance and effectiveness of EFEBs in various fire scenarios representative of commercial vehicles. This dissertation presents original controlled experiments to emulate real-world fire incidents, including controlled fires in confined spaces and dynamic simulations. The experimental approach ensures rigorous evaluation and objective insights into EFEBs’ potential as an autonomous fire suppression system for commercial vehicles. This includes the perspectives of drivers, passengers, fleet operators, insurance agencies, and regulatory bodies. Factors influencing trust, perceived safety, and willingness to adopt EFEBs are analyzed to provide insights into the successful integration of this technology. The findings of this research will contribute to the knowledge of fire safety technology and expand the understanding of the applicability of EFEBs in commercial vehicles.
基金funded by the Innovation-Driven Development Special Fund Project of Guangxi,Grant No.Guike AA22068060the Science and Technology Planning Project of Liuzhou,Grant No.2021AAA0112the Liudong Science and Technology Project,Grant No.20210117.
文摘The extended Kalman filter (EKF) algorithm and acceleration sensor measurements were used to identify vehiclemass and road gradient in the work. Four different states of fixed mass, variable mass, fixed slope and variableslope were set to simulate real-time working conditions, respectively. A comprehensive electric commercial vehicleshifting strategy was formulated according to the identification results. The co-simulation results showed that,compared with the recursive least square (RLS) algorithm, the proposed algorithm could identify the real-timevehicle mass and road gradient quickly and accurately. The comprehensive shifting strategy formulated had thefollowing advantages, e.g., avoiding frequent shifting of vehicles up the hill, making full use ofmotor braking downthe hill, and improving the overall performance of vehicles.
文摘When heavy-duty commercial vehicles(HDCVs)must engage in emergency braking,uncertain conditions such as the brake pressure and road profile variations will inevitably affect braking control.To minimize these uncertainties,we propose a combined longitudinal and lateral controller method based on stochastic model predictive control(SMPC)that is achieved via Chebyshev–Cantelli inequality.In our method,SMPC calculates braking control inputs based on a finite time prediction that is achieved by solving stochastic programming elements,including chance constraints.To accomplish this,SMPC explicitly describes the probabilistic uncertainties to be used when designing a robust control strategy.The main contribution of this paper is the proposal of a braking control formulation that is robust against probabilistic friction circle uncertainty effects.More specifically,the use of Chebyshev–Cantelli inequality suppresses road profile influences,which have characteristics that are different from the Gaussian distribution,thereby improving both braking robustness and control performance against statistical disturbances.Additionally,since the Kalman filtering(KF)algorithm is used to obtain the expectation and covariance used for calculating deterministic transformed chance constraints,the SMPC is reformulated as a KF embedded deterministic MPC.Herein,the effectiveness of our proposed method is verified via a MATLAB/Simulink and TruckSim co-simulation.
文摘今年IAA的口号“Driven by Ideas'(创意驱动)在这场全球最重要的交通、物流和移动性行业贸易展上真正得到了贯彻落实。在汉诺威,未来正在变成看得见的现实。今年IAA的口号“Driven by Ideas”(创意驱动)在这场全球最重要的交通、物流和移动性行业贸易展上真正得到了贯彻落实。在汉诺威,未来正在变成看得见的现实。整个商用车行业向IAA观众展示了创新、创造力和先锋精神。这些品质表现在332款产品的全球首发和1 00多款产品的欧洲首发。此次IAA更是决策者的贸易展,并且国际化程度前所未有。
文摘Obstructive Sleep Apnea (OSA) has been identified by many studies as one of the significant contributing factors for motor vehicle accidents. However, only a small number of studies have been conducted in Malaysia. Objective: This paper aims to highlight the prevalence of OSA among truck drivers and express bus drivers in Malaysia and efforts being undertaken to address issues related to OSA among commercial vehicle drivers. Methodology: Two separate studies were conducted: a cross sectional study among truck drivers and secondly among express bus drivers. The screening process for identifying the high risk group for OSA was done using Berlin questionnaire. Meanwhile, among express bus drivers, OSA was confirmed with sleep study using polysomnography test. Result: Screening of risk group of OSA among truck drivers revealed that 14.6% (19) of drivers were categorized as having high risk of OSA while 85.4% (111) having low risk of OSA. While, in another study, polysomnography test among express bus drivers showed that 83 (28.7%) had mild OSA, 26 (9.0%) had AHI moderate OSA, and 19 drivers (6.6%) severe OSA. Conclusion: This paper highlighted the issues of OSA among commercial vehicle drivers in Malaysia. With an alarming high prevalence, OSA should be a major road safety concern in this country. A special study focusing on sleep and fatigue related crashes may need to be conducted to complement the current studies and full implementation of existing efforts and initiatives to address OSA in road crashes should be realized by the relevant authorities.
文摘Latest data from the China Association of Automobile Manufacturers(CAAM) shows that through 2010.China’s automobile sales surpassed 18 million, breaking the world record of annual auto sales previously held by the United States.Now that China has become a major global auto production player, how is Foton faring? CAAM statistics said production and sales volume of
文摘The heavy-duty vehicle fleet involved in delivering water and sand makes noticeable issues of exhaust emissions and fuel consumption in the process of shale gas development. To examine the possibility of converting these heavy-duty diesel engines to run on natural gas-diesel dual-fuel, a transient engine duty cycle representing the real-world engine working conditions is necessary. In this paper, a methodology is proposed, and a target engine duty cycle comprising of 2231 seconds is developed from on-road data collected from 11 on-road sand and water hauling trucks. The similarity of inherent characteristics of the developed cycle and the base trip observed is evidenced by the 2.05% error of standard deviation and average values for normalized engine speed and engine torque. Our results show that the proposed approach is expected to produce a representative cycle of in-use heavy-duty engine behavior.
文摘为降低重型商用车燃油消耗、减少运输成本,本文协调“人-车-路”交互体系,将车辆与智能网联环境下的多维度信息进行融合,提出了一种基于迭代动态规划(iterative dynamic programming,IDP)的自适应距离域预见性巡航控制策略(adaptive range predictive cruise control strategy,ARPCC)。首先结合车辆状态与前方环境多维度信息,基于车辆纵向动力学建立自适应距离域模型对路网重构,简化网格数量并利用IDP求取全局最优速度序列。其次,在全局最优速度序列的基础上,求取自适应距离域内的分段最优速度序列,实现车辆控制状态的快速求解。最后,利用Matlab/Simulink进行验证。结果表明,通过多次迭代缩小网格,该算法有效提高了计算效率和车辆燃油经济性。
