Currently,the inexorable trend toward the electrification of automobiles has heightened the prominence of road noise within overall vehicle noise.Consequently,an in-depth investigation into automobile road noise holds...Currently,the inexorable trend toward the electrification of automobiles has heightened the prominence of road noise within overall vehicle noise.Consequently,an in-depth investigation into automobile road noise holds substantial practical importance.Previous research endeavors have predominantly centered on the formulation of mechanism models and data-driven models.While mechanism models offer robust controllability,their application encounters challenges in intricate analyses of vehicle body acoustic-vibration coupling,and the effective utilization of accumulated data remains elusive.In contrast,data-driven models exhibit efficient modeling capabilities and can assimilate conceptual vehicle knowledge,but they impose stringent requirements on both data quality and quantity.In response to these considerations,this paper introduces an innovative approach for predicting vehicle road noise by integrating mechanism-driven and data-driven methodologies.Specifically,a series model is devised,amalgamating mechanism analysis with data-driven techniques to predict vehicle interior noise.The simulation results from dynamic models serve as inputs to the data-driven model,ultimately generating outputs through the utilization of the Long Short-Term Memory with Autoencoder(AE-LSTM)architecture.The study subsequently undertakes a comparative analysis between different dynamic models and data-driven models,thereby validating the efficacy of the proposed series vehicle road noise prediction model.This series model,encapsulating the rigid-flexible coupling dynamic model and AE-LSTM series model,not only demonstrates heightened computational efficiency but also attains superior prediction accuracy.展开更多
The fundamental research on thermo-mechanical conditions provides an experimental basis for high-performance Mg-Al-Ca-Mn alloys.However, there is a lack of systematical investigation for this series alloys on the hot-...The fundamental research on thermo-mechanical conditions provides an experimental basis for high-performance Mg-Al-Ca-Mn alloys.However, there is a lack of systematical investigation for this series alloys on the hot-deformation kinetics and extrusion parameter optimization. Here, the flow behavior, constitutive model, dynamic recrystallization(DRX) kinetic model and processing map of a dilute rare-earth free Mg-1.3Al-0.4Ca-0.4Mn(AXM100, wt.%) alloy were studied under different hot-compressive conditions. In addition, the extrusion parameter optimization of this alloy was performed based on the hot-processing map. The results showed that the conventional Arrhenius-type strain-related constitutive model only worked well for the flow curves at high temperatures and low strain rates. In comparison, using the machine learning assisted model(support vector regression, SVR) could effectively improve the accuracy between the predicted and experimental values. The DRX kinetic model was established, and a typical necklace-shaped structure preferentially occurred at the original grain boundaries and the second phases. The DRX nucleation weakened the texture intensity, and the further growth caused the more scattered basal texture. The hot-processing maps at different strains were also measured and the optimal hot-processing range could be confirmed at the deformation temperatures of 600~723 K and the strain rates of 0.018~0.563 s^(-1). Based on the optimum hot-processing range, a suitable extrusion parameter was considered as 603 K and 0.1 mm/s and the as-extruded alloy in this parameter exhibited a good strength-ductility synergy(yield strength of ~ 232.1 MPa, ultimate strength of ~ 278.2 MPa and elongation-to-failure of ~ 20.1%). Finally, the strengthening-plasticizing mechanisms and the relationships between the DRXed grain size, yield strength and extrusion parameters were analyzed.展开更多
Polygonal wear seriously decreases the lifespan of a tire of a passenger car and adversely affects vehicle dynamic safety.The present paper builds a model that reflects the dynamic contact characteristics of the tire ...Polygonal wear seriously decreases the lifespan of a tire of a passenger car and adversely affects vehicle dynamic safety.The present paper builds a model that reflects the dynamic contact characteristics of the tire and reveals the mechanism and conditions of polygonal wear of a tire.The model describes the dynamic contact behavior of the tread block and considers the characteristics of dynamic friction between the road and tread of a rolling tire.Conducting numerical bifurcation analysis,the paper reveals the conditions for self-excited vibration of the tread,i.e.,the improper combination of the vertical load,wheel slip angle,tire pressure and vehicle speed considerably strengthen the lateral self-excited vibration of the tread,which is the direct vibrational source of abnormal circumferential polygonal wear.The polygonal wear of a tire occurs when a vehicle travels for a certain long distance at a so-called polygonal wear speed.The polygonal wear speed should induce lateral self-excited vibration on the contact tread of the tire and the frequency of the lateral self-excited vibration should be divisible by the rolling frequency of tire that is determined by the polygonal wear speed.Visible polygonal wear requires that the vehicle travels at a certain polygonal wear speed for a minimal distance to produce a stably developing polygonal wear pattern even for subsequent driving at variable speed.展开更多
基金funded by the SWJTU Science and Technology Innovation Project,Grant Number 2682022CX008the Natural Science Foundation of Sichuan Province,Grant Number 2022NSFSC1892.
文摘Currently,the inexorable trend toward the electrification of automobiles has heightened the prominence of road noise within overall vehicle noise.Consequently,an in-depth investigation into automobile road noise holds substantial practical importance.Previous research endeavors have predominantly centered on the formulation of mechanism models and data-driven models.While mechanism models offer robust controllability,their application encounters challenges in intricate analyses of vehicle body acoustic-vibration coupling,and the effective utilization of accumulated data remains elusive.In contrast,data-driven models exhibit efficient modeling capabilities and can assimilate conceptual vehicle knowledge,but they impose stringent requirements on both data quality and quantity.In response to these considerations,this paper introduces an innovative approach for predicting vehicle road noise by integrating mechanism-driven and data-driven methodologies.Specifically,a series model is devised,amalgamating mechanism analysis with data-driven techniques to predict vehicle interior noise.The simulation results from dynamic models serve as inputs to the data-driven model,ultimately generating outputs through the utilization of the Long Short-Term Memory with Autoencoder(AE-LSTM)architecture.The study subsequently undertakes a comparative analysis between different dynamic models and data-driven models,thereby validating the efficacy of the proposed series vehicle road noise prediction model.This series model,encapsulating the rigid-flexible coupling dynamic model and AE-LSTM series model,not only demonstrates heightened computational efficiency but also attains superior prediction accuracy.
基金funded by the Postgraduate Research & Practice Innovation Program of Jiangsu Province (No.SJCX22_1720)the National Natural Science Foundation of China (No.51901204)+1 种基金the Chongqing Science and Technology Commission (Nos.cstc2020jcyj-msxmX0184 and cstc2019jscx-mbdxX0031)the University Innovation Research Group of Chongqing (No.CXQT20023)。
文摘The fundamental research on thermo-mechanical conditions provides an experimental basis for high-performance Mg-Al-Ca-Mn alloys.However, there is a lack of systematical investigation for this series alloys on the hot-deformation kinetics and extrusion parameter optimization. Here, the flow behavior, constitutive model, dynamic recrystallization(DRX) kinetic model and processing map of a dilute rare-earth free Mg-1.3Al-0.4Ca-0.4Mn(AXM100, wt.%) alloy were studied under different hot-compressive conditions. In addition, the extrusion parameter optimization of this alloy was performed based on the hot-processing map. The results showed that the conventional Arrhenius-type strain-related constitutive model only worked well for the flow curves at high temperatures and low strain rates. In comparison, using the machine learning assisted model(support vector regression, SVR) could effectively improve the accuracy between the predicted and experimental values. The DRX kinetic model was established, and a typical necklace-shaped structure preferentially occurred at the original grain boundaries and the second phases. The DRX nucleation weakened the texture intensity, and the further growth caused the more scattered basal texture. The hot-processing maps at different strains were also measured and the optimal hot-processing range could be confirmed at the deformation temperatures of 600~723 K and the strain rates of 0.018~0.563 s^(-1). Based on the optimum hot-processing range, a suitable extrusion parameter was considered as 603 K and 0.1 mm/s and the as-extruded alloy in this parameter exhibited a good strength-ductility synergy(yield strength of ~ 232.1 MPa, ultimate strength of ~ 278.2 MPa and elongation-to-failure of ~ 20.1%). Finally, the strengthening-plasticizing mechanisms and the relationships between the DRXed grain size, yield strength and extrusion parameters were analyzed.
基金The authors acknowledge financial support from the National Natural Science Foundation of China(Grant Numbers 51375343,50775162 and 51305303).
文摘Polygonal wear seriously decreases the lifespan of a tire of a passenger car and adversely affects vehicle dynamic safety.The present paper builds a model that reflects the dynamic contact characteristics of the tire and reveals the mechanism and conditions of polygonal wear of a tire.The model describes the dynamic contact behavior of the tread block and considers the characteristics of dynamic friction between the road and tread of a rolling tire.Conducting numerical bifurcation analysis,the paper reveals the conditions for self-excited vibration of the tread,i.e.,the improper combination of the vertical load,wheel slip angle,tire pressure and vehicle speed considerably strengthen the lateral self-excited vibration of the tread,which is the direct vibrational source of abnormal circumferential polygonal wear.The polygonal wear of a tire occurs when a vehicle travels for a certain long distance at a so-called polygonal wear speed.The polygonal wear speed should induce lateral self-excited vibration on the contact tread of the tire and the frequency of the lateral self-excited vibration should be divisible by the rolling frequency of tire that is determined by the polygonal wear speed.Visible polygonal wear requires that the vehicle travels at a certain polygonal wear speed for a minimal distance to produce a stably developing polygonal wear pattern even for subsequent driving at variable speed.
