Due to the complicated three-dimensional behaviors and testing limitations of reinforced concrete(RC)members in torsion,torsional mechanism exploration and torsional performance prediction have always been difficult.I...Due to the complicated three-dimensional behaviors and testing limitations of reinforced concrete(RC)members in torsion,torsional mechanism exploration and torsional performance prediction have always been difficult.In the present paper,several machine learning models were applied to predict the torsional capacity of RC members.Experimental results of a total of 287 torsional specimens were collected through an overall literature review.Algorithms of extreme gradient boosting machine(XGBM),random forest regression,back propagation artificial neural network and support vector machine,were trained and tested by 10-fold cross-validation method.Predictive performances of proposed machine learning models were evaluated and compared,both with each other and with the calculated results of existing design codes,i.e.,GB 50010,ACI 318-19,and Eurocode 2.The results demonstrated that better predictive performance was achieved by machine learning models,whereas GB 50010 slightly overestimated the torsional capacity,and ACI 318-19 and Eurocode 2 underestimated it,especially in the case of ACI 318-19.The XGBM model gave the most favorable predictions with R^(2)=0.999,RMSE=1.386,MAE=0.86,andλ=0.976.Moreover,strength of concrete was the most sensitive input parameters affecting the reliability of the predictive model,followed by transverse-to-longitudinal reinforcement ratio and total reinforcement ratio.展开更多
Much progress has been made in the development of automotive transmissions over the past 20 years,e.g.,an increased speed number,expanded ratio spread and improved efficiency and shift quality.Automotive transmissions...Much progress has been made in the development of automotive transmissions over the past 20 years,e.g.,an increased speed number,expanded ratio spread and improved efficiency and shift quality.Automotive transmissions are moving toward electrification in response to stringent legislation on emissions and the pressing demand for better fuel economy.This paper reviews progress in automotive transmission technology.Assisted by computer-aided programs,new transmission schemes are constantly being developed.We therefore first introduce the synthesis of the transmission scheme and parameter optimization.We then discuss the progress in the transmission technology of a conventional internal combustion engine vehicle in terms of new layouts;improved efficiency;noise,vibration and harshness technology;and the shifting strategy and control technology.As the major development trend,transmission electrification is subsequently discussed;this discussion includes the configuration design,energy management strategy,hybrid mode shifting control,single-speed and multi-speed electric vehicle transmission and distributed electric drive.Finally,a summary and outlook are presented for conventional automotive transmissions,hybrid transmissions and electric vehicle transmissions.展开更多
As a vital vehicle part,the powertrain system is undergoing a fast transition towards electrification.The new integrated electric drive system has been widely used,especially for passenger cars.In this work,a novel el...As a vital vehicle part,the powertrain system is undergoing a fast transition towards electrification.The new integrated electric drive system has been widely used,especially for passenger cars.In this work,a novel electric dual motor transmission is proposed for heavy commercial vehicles.The transmission scheme is firstly introduced,which can achieve 9 different operating modes including 5 single motor modes and 4 dual motor modes.Then,the mode shift map with minimum energy consumption is designed based on the motor efficiency map and the proposed energy management strategy.The driving power is appropriately distributed between the two motors in dual motor modes under the condition of minimum power consumption.In addition,a coordinated control strategy is developed for mode shift control without power interruption.The results show that the electric dual motor transmission has advantages in power consumption and power shift ability compared with the conventional single motor automated manual transmission.展开更多
What is the biggest challenge when vehicles move towards electrification?Electric drive system responds positively to this question,which plays a key role in terms of energy sav-ing and carbon emission reduction.Besid...What is the biggest challenge when vehicles move towards electrification?Electric drive system responds positively to this question,which plays a key role in terms of energy sav-ing and carbon emission reduction.Besides,it is required to provide excellent driving performance,therefore becoming a hot topic in the automotive field.Hence Automotive Innova-tion proposed this special issue.展开更多
基金The authors are extremely grateful to the funds including the National Natural Science Foundation of China(Grant No.51808258)the Fundamental Research Funds for the Central Universities(No.2022QN1031).
文摘Due to the complicated three-dimensional behaviors and testing limitations of reinforced concrete(RC)members in torsion,torsional mechanism exploration and torsional performance prediction have always been difficult.In the present paper,several machine learning models were applied to predict the torsional capacity of RC members.Experimental results of a total of 287 torsional specimens were collected through an overall literature review.Algorithms of extreme gradient boosting machine(XGBM),random forest regression,back propagation artificial neural network and support vector machine,were trained and tested by 10-fold cross-validation method.Predictive performances of proposed machine learning models were evaluated and compared,both with each other and with the calculated results of existing design codes,i.e.,GB 50010,ACI 318-19,and Eurocode 2.The results demonstrated that better predictive performance was achieved by machine learning models,whereas GB 50010 slightly overestimated the torsional capacity,and ACI 318-19 and Eurocode 2 underestimated it,especially in the case of ACI 318-19.The XGBM model gave the most favorable predictions with R^(2)=0.999,RMSE=1.386,MAE=0.86,andλ=0.976.Moreover,strength of concrete was the most sensitive input parameters affecting the reliability of the predictive model,followed by transverse-to-longitudinal reinforcement ratio and total reinforcement ratio.
基金the National Key R&D Program of China“Development and Vehicle Integration of Cost-effective Commercial Vehicle Hybrid System”(Grant No.2018YFB0105900).
文摘Much progress has been made in the development of automotive transmissions over the past 20 years,e.g.,an increased speed number,expanded ratio spread and improved efficiency and shift quality.Automotive transmissions are moving toward electrification in response to stringent legislation on emissions and the pressing demand for better fuel economy.This paper reviews progress in automotive transmission technology.Assisted by computer-aided programs,new transmission schemes are constantly being developed.We therefore first introduce the synthesis of the transmission scheme and parameter optimization.We then discuss the progress in the transmission technology of a conventional internal combustion engine vehicle in terms of new layouts;improved efficiency;noise,vibration and harshness technology;and the shifting strategy and control technology.As the major development trend,transmission electrification is subsequently discussed;this discussion includes the configuration design,energy management strategy,hybrid mode shifting control,single-speed and multi-speed electric vehicle transmission and distributed electric drive.Finally,a summary and outlook are presented for conventional automotive transmissions,hybrid transmissions and electric vehicle transmissions.
基金This work is financially supported by The 2025 Science and Technology Innovation Program of Ningbo“R&D of Key Technologies for Electric Vehicle Range Extenders”(Grant No.2019B10111),National Natural Science Foundation of China(NSFC,Grant No.52072018)Key Science and Technology Innovation Project of Shandong Province(Grant No.2019JZZY010913)Key Science and Technology Project of Guangxi Province(Grant No.AA19254013).
文摘As a vital vehicle part,the powertrain system is undergoing a fast transition towards electrification.The new integrated electric drive system has been widely used,especially for passenger cars.In this work,a novel electric dual motor transmission is proposed for heavy commercial vehicles.The transmission scheme is firstly introduced,which can achieve 9 different operating modes including 5 single motor modes and 4 dual motor modes.Then,the mode shift map with minimum energy consumption is designed based on the motor efficiency map and the proposed energy management strategy.The driving power is appropriately distributed between the two motors in dual motor modes under the condition of minimum power consumption.In addition,a coordinated control strategy is developed for mode shift control without power interruption.The results show that the electric dual motor transmission has advantages in power consumption and power shift ability compared with the conventional single motor automated manual transmission.
文摘What is the biggest challenge when vehicles move towards electrification?Electric drive system responds positively to this question,which plays a key role in terms of energy sav-ing and carbon emission reduction.Besides,it is required to provide excellent driving performance,therefore becoming a hot topic in the automotive field.Hence Automotive Innova-tion proposed this special issue.