The current research on the integrity of critical structures of rail vehicles mainly focuses on the design stage,which needs an effective method for assessing the service state.This paper proposes a framework for pred...The current research on the integrity of critical structures of rail vehicles mainly focuses on the design stage,which needs an effective method for assessing the service state.This paper proposes a framework for predicting the remaining useful life(RUL)of in-service structures with and without visible cracks.The hypothetical distribution and delay time models were used to apply the equivalent crack growth life data of heavy-duty railway cast steel knuckles,which revealed the evolution characteristics of the crack length and life scores of the knuckle under different fracture failure modes.The results indicate that the method effectively predicts the RUL of service knuckles in different failure modes based on the cumulative failure probability curves for different locations and surface crack lengths.This study proposes an RUL prediction framework that supports the dynamic overhaul and state maintenance of knuckle fatigue cracks.展开更多
Fuel consumption is one of the main concerns for heavy-duty trucks.Predictive cruise control(PCC)provides an intriguing opportunity to reduce fuel consumption by using the upcoming road information.In this study,a rea...Fuel consumption is one of the main concerns for heavy-duty trucks.Predictive cruise control(PCC)provides an intriguing opportunity to reduce fuel consumption by using the upcoming road information.In this study,a real-time implementable PCC,which simultaneously optimizes engine torque and gear shifting,is proposed for heavy-duty trucks.To minimize fuel consumption,the problem of the PCC is formulated as a nonlinear model predictive control(MPC),in which the upcoming road elevation information is used.Finding the solution of the nonlinear MPC is time consuming;thus,a real-time implementable solver is developed based on Pontryagin’s maximum principle and indirect shooting method.Dynamic programming(DP)algorithm,as a global optimization algorithm,is used as a performance benchmark for the proposed solver.Simulation,hardware-in-the-loop and real-truck experiments are conducted to verify the performance of the proposed controller.The results demonstrate that the MPC-based solution performs nearly as well as the DP-based solution,with less than 1%deviation for testing roads.Moreover,the proposed co-optimization controller is implementable in a real-truck,and the proposed MPC-based PCC algorithm achieves a fuel-saving rate of 7.9%without compromising the truck’s travel time.展开更多
In this study,a human-sensitive frequency band vibration isolator(HFBVI)with quasi-zero stiffness(QZS)characteristics for heavy-duty truck seats is designed to improve the comfort of heavy-duty truck drivers on uneven...In this study,a human-sensitive frequency band vibration isolator(HFBVI)with quasi-zero stiffness(QZS)characteristics for heavy-duty truck seats is designed to improve the comfort of heavy-duty truck drivers on uneven roads.First,the analytical expressions for the force and displacement of the HFBVI are derived with the Lagrange equation and d'Alembert's principle,and are validated through the prototype restoring force testing.Second,the harmonic balance method(HBM)is used to obtain the dynamic responses under harmonic excitation,and further the influence of pre-stretching on the dynamic characteristics and transmissibility is discussed.Finally,the experimental prototype of the HFBVI is fabricated,and vibration experiments are conducted under harmonic excitation to verify the vibration isolation performance(VIP)of the proposed vibration isolator.The experimental results indicate that the HFBVI can effectively suppress the frequency band(4-8 Hz)to which the human body is sensitive to vertical vibration.In addition,under real random road spectrum excitation,the HFBVI can achieve low-frequency vibration isolation close to 2 Hz,providing new prospects for ensuring the health of heavy-duty truck drivers.展开更多
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
A robust parameter identification method based on Kiencke model was proposed to solve the problem of the parameter identification accuracy being affected by the rail environment change and noise interference for heavy...A robust parameter identification method based on Kiencke model was proposed to solve the problem of the parameter identification accuracy being affected by the rail environment change and noise interference for heavy-duty trains. Firstly, a Kiencke stick-creep identification model was constructed, and the parameter identification task was transformed into a quadratic programming problem. Secondly, an iterative algorithm was constructed to solve the problem, into which a time-varying forgetting factor was added to track the change of the rail environment, and to solve the uncertainty problem of the wheel-rail environment. The Granger causality test was adopted to detect the interference, and then the weights of the current data were redistributed to solve the problem of noise interference in parameter identification. Finally, simulations were carried out and the results showed that the proposed method could track the change of the track environment in time, reduce the noise interference in the identification process, and effectively identify the adhesion performance parameters.展开更多
基金Supported by National Natural Science Foundation of China (Grant No.52175123)Sichuan Provincial Outstanding Youth Fund (Grant No.22JDJQ0025)Independent Exploration Project of State Key Laboratory of Railway Transit Vehicle System (Grant No.2024RVL-T03)。
文摘The current research on the integrity of critical structures of rail vehicles mainly focuses on the design stage,which needs an effective method for assessing the service state.This paper proposes a framework for predicting the remaining useful life(RUL)of in-service structures with and without visible cracks.The hypothetical distribution and delay time models were used to apply the equivalent crack growth life data of heavy-duty railway cast steel knuckles,which revealed the evolution characteristics of the crack length and life scores of the knuckle under different fracture failure modes.The results indicate that the method effectively predicts the RUL of service knuckles in different failure modes based on the cumulative failure probability curves for different locations and surface crack lengths.This study proposes an RUL prediction framework that supports the dynamic overhaul and state maintenance of knuckle fatigue cracks.
基金Supported by International Technology Cooperation Program of Science and Technology Commission of Shanghai Municipality of China(Grant No.21160710600)National Nature Science Foundation of China(Grant No.52372393)Shanghai Pujiang Program of China(Grant No.21PJD075).
文摘Fuel consumption is one of the main concerns for heavy-duty trucks.Predictive cruise control(PCC)provides an intriguing opportunity to reduce fuel consumption by using the upcoming road information.In this study,a real-time implementable PCC,which simultaneously optimizes engine torque and gear shifting,is proposed for heavy-duty trucks.To minimize fuel consumption,the problem of the PCC is formulated as a nonlinear model predictive control(MPC),in which the upcoming road elevation information is used.Finding the solution of the nonlinear MPC is time consuming;thus,a real-time implementable solver is developed based on Pontryagin’s maximum principle and indirect shooting method.Dynamic programming(DP)algorithm,as a global optimization algorithm,is used as a performance benchmark for the proposed solver.Simulation,hardware-in-the-loop and real-truck experiments are conducted to verify the performance of the proposed controller.The results demonstrate that the MPC-based solution performs nearly as well as the DP-based solution,with less than 1%deviation for testing roads.Moreover,the proposed co-optimization controller is implementable in a real-truck,and the proposed MPC-based PCC algorithm achieves a fuel-saving rate of 7.9%without compromising the truck’s travel time.
基金supported by the National Natural Science Foundation of China(No.12172226)。
文摘In this study,a human-sensitive frequency band vibration isolator(HFBVI)with quasi-zero stiffness(QZS)characteristics for heavy-duty truck seats is designed to improve the comfort of heavy-duty truck drivers on uneven roads.First,the analytical expressions for the force and displacement of the HFBVI are derived with the Lagrange equation and d'Alembert's principle,and are validated through the prototype restoring force testing.Second,the harmonic balance method(HBM)is used to obtain the dynamic responses under harmonic excitation,and further the influence of pre-stretching on the dynamic characteristics and transmissibility is discussed.Finally,the experimental prototype of the HFBVI is fabricated,and vibration experiments are conducted under harmonic excitation to verify the vibration isolation performance(VIP)of the proposed vibration isolator.The experimental results indicate that the HFBVI can effectively suppress the frequency band(4-8 Hz)to which the human body is sensitive to vertical vibration.In addition,under real random road spectrum excitation,the HFBVI can achieve low-frequency vibration isolation close to 2 Hz,providing new prospects for ensuring the health of heavy-duty truck drivers.
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.
文摘A robust parameter identification method based on Kiencke model was proposed to solve the problem of the parameter identification accuracy being affected by the rail environment change and noise interference for heavy-duty trains. Firstly, a Kiencke stick-creep identification model was constructed, and the parameter identification task was transformed into a quadratic programming problem. Secondly, an iterative algorithm was constructed to solve the problem, into which a time-varying forgetting factor was added to track the change of the rail environment, and to solve the uncertainty problem of the wheel-rail environment. The Granger causality test was adopted to detect the interference, and then the weights of the current data were redistributed to solve the problem of noise interference in parameter identification. Finally, simulations were carried out and the results showed that the proposed method could track the change of the track environment in time, reduce the noise interference in the identification process, and effectively identify the adhesion performance parameters.
