{"title":"Shifting control optimisation of automatic transmission with congested conditions identification based on the support vector machine","authors":"Minkai Jiang, Lijuan Ju, Kaixuan Chen, Guangqiang Wu, Shang Peng","doi":"10.1504/ijvp.2023.10053786","DOIUrl":"https://doi.org/10.1504/ijvp.2023.10053786","url":null,"abstract":"","PeriodicalId":52169,"journal":{"name":"International Journal of Vehicle Performance","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66690544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1504/ijvp.2023.10055489
Xiujian Yang, Peng Zhou, Tao Wu, Rong Dai, Jiaqi Liu
{"title":"Reliability optimisation of an electric bus frame orienting side impact safety and lightweight","authors":"Xiujian Yang, Peng Zhou, Tao Wu, Rong Dai, Jiaqi Liu","doi":"10.1504/ijvp.2023.10055489","DOIUrl":"https://doi.org/10.1504/ijvp.2023.10055489","url":null,"abstract":"","PeriodicalId":52169,"journal":{"name":"International Journal of Vehicle Performance","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66690678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1504/ijvp.2023.10055674
B. Schick, A. Lion, R. Schurmann, Philipp Rupp
{"title":"Objectification and prediction of the subjective criticality of axle damages using artificial neural networks as well as multibody- and real-time simulations","authors":"B. Schick, A. Lion, R. Schurmann, Philipp Rupp","doi":"10.1504/ijvp.2023.10055674","DOIUrl":"https://doi.org/10.1504/ijvp.2023.10055674","url":null,"abstract":"","PeriodicalId":52169,"journal":{"name":"International Journal of Vehicle Performance","volume":"46 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66690821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Optimisation study of aerodynamic drag based on flow field topology in box-type trucks","authors":"Zigang Zhao, Hongwei Zhang, Wangyang Xiang, Zihou Yuan","doi":"10.1504/ijvp.2023.10058001","DOIUrl":"https://doi.org/10.1504/ijvp.2023.10058001","url":null,"abstract":"","PeriodicalId":52169,"journal":{"name":"International Journal of Vehicle Performance","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66690896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1504/ijvp.2023.10053636
S. Mondal, Amit Kumar, A. Tiwary
{"title":"An experimental investigation on exhaust heat recovery system of the gasoline driven vehicle for space conditioning applications","authors":"S. Mondal, Amit Kumar, A. Tiwary","doi":"10.1504/ijvp.2023.10053636","DOIUrl":"https://doi.org/10.1504/ijvp.2023.10053636","url":null,"abstract":"","PeriodicalId":52169,"journal":{"name":"International Journal of Vehicle Performance","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66690974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1504/ijvp.2023.128067
Carlos Armenta Déu, Erwan Cattin
The main goal of this paper is the development of a method that allows a control system to determine the electric vehicle (EV) driving range within the highest precision. The methodology has been developed for real driving conditions taking into account not only the kind of driving but also the road characteristics and the driving operational mode. Battery capacity change with discharge has been considered for the available energy. A simulation process has been developed to reproduce the driving characteristics of a daily trip considering the dynamic conditions and vehicle characteristics such as size, shape and mass. Five different driving modes are included in the study, acceleration, deceleration, constant speed, ascent and descent. Specific software has been developed to predict electric vehicle range under real driving conditions as a function of the characteristic parameters of a daily trip.
{"title":"A new method to determine electric vehicle range in real driving conditions","authors":"Carlos Armenta Déu, Erwan Cattin","doi":"10.1504/ijvp.2023.128067","DOIUrl":"https://doi.org/10.1504/ijvp.2023.128067","url":null,"abstract":"The main goal of this paper is the development of a method that allows a control system to determine the electric vehicle (EV) driving range within the highest precision. The methodology has been developed for real driving conditions taking into account not only the kind of driving but also the road characteristics and the driving operational mode. Battery capacity change with discharge has been considered for the available energy. A simulation process has been developed to reproduce the driving characteristics of a daily trip considering the dynamic conditions and vehicle characteristics such as size, shape and mass. Five different driving modes are included in the study, acceleration, deceleration, constant speed, ascent and descent. Specific software has been developed to predict electric vehicle range under real driving conditions as a function of the characteristic parameters of a daily trip.","PeriodicalId":52169,"journal":{"name":"International Journal of Vehicle Performance","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134996513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1504/ijvp.2023.133854
Robert Schurmann, Alexander Lion, Bernhard Schick, Philipp Rupp
For the assessment of axle damages, real vehicle tests have mostly been used so far, but they are dangerous and difficult to reproduce. Therefore, driving simulators are becoming increasingly important for the virtual rating of vehicles. Regardless of whether a real vehicle or a driving simulator is used, the prediction of the subjective perception of axle damages requires time-consuming driving tests. A powerful dynamic driving simulator is used to obtain subjective evaluations of various axle damages. Objective vehicle quantities are logged simultaneously. Subsequently, multilinear regression (MLR) models and artificial neural networks (ANN) are used to identify correlations and predict subjective evaluations based on objective data. Furthermore, real-time capable vehicle models in CarMaker and multibody dynamic (MBD) models in ADAMS/Car are used to virtually carry out driving manoeuvres and generate synthetic data. By combining the simulated vehicle data with an ANN, subjective driver evaluations can be predicted entirely virtual.
{"title":"Objectification and prediction of the subjective criticality of axle damages using artificial neural networks as well as multibody- and real-time simulations","authors":"Robert Schurmann, Alexander Lion, Bernhard Schick, Philipp Rupp","doi":"10.1504/ijvp.2023.133854","DOIUrl":"https://doi.org/10.1504/ijvp.2023.133854","url":null,"abstract":"For the assessment of axle damages, real vehicle tests have mostly been used so far, but they are dangerous and difficult to reproduce. Therefore, driving simulators are becoming increasingly important for the virtual rating of vehicles. Regardless of whether a real vehicle or a driving simulator is used, the prediction of the subjective perception of axle damages requires time-consuming driving tests. A powerful dynamic driving simulator is used to obtain subjective evaluations of various axle damages. Objective vehicle quantities are logged simultaneously. Subsequently, multilinear regression (MLR) models and artificial neural networks (ANN) are used to identify correlations and predict subjective evaluations based on objective data. Furthermore, real-time capable vehicle models in CarMaker and multibody dynamic (MBD) models in ADAMS/Car are used to virtually carry out driving manoeuvres and generate synthetic data. By combining the simulated vehicle data with an ANN, subjective driver evaluations can be predicted entirely virtual.","PeriodicalId":52169,"journal":{"name":"International Journal of Vehicle Performance","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136003513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1504/ijvp.2023.10053885
M. Karimi, Sabah Khan, Salma Khatoon
{"title":"Dual evaporator system as an alternative for air-conditioning and refrigeration in automobiles","authors":"M. Karimi, Sabah Khan, Salma Khatoon","doi":"10.1504/ijvp.2023.10053885","DOIUrl":"https://doi.org/10.1504/ijvp.2023.10053885","url":null,"abstract":"","PeriodicalId":52169,"journal":{"name":"International Journal of Vehicle Performance","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66690558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1504/ijvp.2023.131974
Kaixuan Chen, Guangqiang Wu, Shang Peng, Xiang Zeng, Lijuan Ju
This paper proposes a speed strategy based on reinforcement learning on the basis of double traffic lights. This strategy can ensure that vehicles can pass traffic lights without stopping or with little stopping. First of all, Prescan software is used to build traffic lights, roads, and vehicles and other scenario models. Simulink software is used for vehicles, traffic lights control, and other models. Secondly, the double traffic lights scenario has analysed in detail. And then, the improved Q-learning algorithm is used to build the vehicle speed decision model and train the Q table. Q table is used for subsequent real vehicle tests and simulation verification. Finally, the feasibility of the strategy is verified in a variety of conditions, and the results show that the strategy can guarantee fuel economy and get through the double traffic lights as smoothly as possible.
{"title":"The vehicle speed strategy with double traffic lights based on reinforcement learning","authors":"Kaixuan Chen, Guangqiang Wu, Shang Peng, Xiang Zeng, Lijuan Ju","doi":"10.1504/ijvp.2023.131974","DOIUrl":"https://doi.org/10.1504/ijvp.2023.131974","url":null,"abstract":"This paper proposes a speed strategy based on reinforcement learning on the basis of double traffic lights. This strategy can ensure that vehicles can pass traffic lights without stopping or with little stopping. First of all, Prescan software is used to build traffic lights, roads, and vehicles and other scenario models. Simulink software is used for vehicles, traffic lights control, and other models. Secondly, the double traffic lights scenario has analysed in detail. And then, the improved Q-learning algorithm is used to build the vehicle speed decision model and train the Q table. Q table is used for subsequent real vehicle tests and simulation verification. Finally, the feasibility of the strategy is verified in a variety of conditions, and the results show that the strategy can guarantee fuel economy and get through the double traffic lights as smoothly as possible.","PeriodicalId":52169,"journal":{"name":"International Journal of Vehicle Performance","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135733905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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