2022 IEEE 1st International Conference on Cognitive Mobility (CogMob)最新文献

{"title":"Temperature Prediction of Automotive Battery Systems under Realistic Driving Conditions using Artificial Neural Networks","authors":"Johannes Liebertseder, Susann Wunsch, Christine Sonner, L. Berg, M. Doppelbauer, J. Tübke","doi":"10.1109/CogMob55547.2022.10118237","DOIUrl":"https://doi.org/10.1109/CogMob55547.2022.10118237","url":null,"abstract":"The accurate prediction of the battery temperature in an electric vehicle is crucial for an effective thermal management of the battery system. Here, a nonlinear autoregressive exogenous network is used to model the complex thermal behavior of a battery cell. It is trained with conventional driving data and uses input parameters that are easy to obtain. Its accuracy is proven for a wide range of temperatures, showing the simple, general and robust applicability of the approach.","PeriodicalId":430975,"journal":{"name":"2022 IEEE 1st International Conference on Cognitive Mobility (CogMob)","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116374503","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":"An investigation of sustainable technologies in the field of electric mobility","authors":"Tibor Vajsz, C. Horváth, Attila Geleta, Viktor Wendler, Roland Péter Bálint, Márk Neumayer, Donát Zoltán Varga","doi":"10.1109/CogMob55547.2022.10118323","DOIUrl":"https://doi.org/10.1109/CogMob55547.2022.10118323","url":null,"abstract":"Electric vehicles are well-known for their excellent energy-efficiency and locally zero CO2 emissions. Although, this is a significant step towards carbon-neutrality, other possible, indirect sources of emissions like electricity-generation and production must also be investigated for their CO2 emissions in order to determine the environmental-friendliness of electric vehicles. Waste generation and recyclability related to the main electric vehicle components (i.e., high-voltage battery system, electric motor drive system) is another important topic that must be carefully examined as well. The definition of the “0 km” footstep plays an important role in determining the future path towards carbon-neutrality and it is also an essential term for decarbonization related lawmaking. This paper deals with the investigation of the environmental footprint of electric vehicles along with the study of more sustainable technologies that can further improve the recyclability of the main electric vehicle components and thus the eco-friendliness of electric vehicles. A detailed analysis is carried for these topics in order to propose solutions for accelerating the way towards carbon-neutrality. Besides the technical aspects, other factors such as economy, ecological concerns, geographical distribution of certain materials, and thus geopolitical problems are also taken into account. Synthetic fuels are interesting candidates in the case of marine applications and aviation to make these fields carbon-neutral, so they are also investigated in this paper, including their overall fit into the future of mobility. Based on the wide-range analysis a prediction is made for the expected future trends of electric vehicle technologies and beside that other carbon-neutral solutions.","PeriodicalId":430975,"journal":{"name":"2022 IEEE 1st International Conference on Cognitive Mobility (CogMob)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122350336","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":"Inductance tensor calculation method for characterizing synchronous reluctance machines","authors":"Vilmos Paiss, Richard Csaba Kovacs","doi":"10.1109/CogMob55547.2022.10118014","DOIUrl":"https://doi.org/10.1109/CogMob55547.2022.10118014","url":null,"abstract":"Synchronous reluctance traction machines are becoming more and more important participants of electromobility due to the increasing demand to reduce the amount of the rare-earth materials in the electric vehicle components. With reducing rare earth material consumption, the economic and ecological risks of the future in e-mobility can partially be prevented. Without permanent magnet the electrical motor design requires a disruptive concept, which can compensate the lack of the most efficient type of motor component with good efficiency performance at the operating points. For instance, even the lower torque density and vehicle acceleration requirements of a city car design can be rationally acceptable if the reduced ecological footprint of the traction motor is more dominated than the driving experience as the cognitive engineering prefers the vehicle test cycle of a green driver instead of a racing driver. More innovative engineering cogitation is expected for designing a motor layout of a synchronous reluctance machines, which possesses more significant non-linear behavior and technical challenges regarding the drive control than the permanent magnet synchronous machines. To describe the non-fundamental motor behavior, the inductance tensor of the motor must be determined in a multi-variable parameter-field over the time domain. Since the inductance tensor maps cannot be directly evaluated from the FEA software, therefore this paper presents a novel inductance tensor map postprocessing method of FE analysis based on the differential inductances. The co-energy-based force method coupled with the number of divisions of rotor displacement, prescribes the resolution of required inductance map. The reduction of the non-linear effects by modifying the current profiles via the motor control can be satisfied only with a well-defined tensor mapping method. A properly determined motor model together with the corresponding control compensation method can further improve the efficiency of synchronous reluctance motors and provide the required performance at low speed and partial load domain, where the real operating points of an ordinary used vehicle can be found.","PeriodicalId":430975,"journal":{"name":"2022 IEEE 1st International Conference on Cognitive Mobility (CogMob)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130721543","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":"Evaluating of E-Vehicle Gear Noise","authors":"M. Zöldy, Zoltán Pathy-Nagy","doi":"10.1109/CogMob55547.2022.10117985","DOIUrl":"https://doi.org/10.1109/CogMob55547.2022.10117985","url":null,"abstract":"E-mobility role will be increasing in the next decades, and it has fundamentally different approaches than previous technologies. The aim of this research was to set up a measurement system for the evaluation of the gear noises of a premium vehicle. The measurements showed that with the use of a fast and simple instrumentation, a detailed sound analysis can be created, if the right measuring and analysis system is used. During the acceleration phase, the dominant gear mesh orders at the outside of the vehicle were almost inaudible.","PeriodicalId":430975,"journal":{"name":"2022 IEEE 1st International Conference on Cognitive Mobility (CogMob)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124386135","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":"Two state dual loop EGR engine model","authors":"Á. Nyerges","doi":"10.1109/CogMob55547.2022.10118110","DOIUrl":"https://doi.org/10.1109/CogMob55547.2022.10118110","url":null,"abstract":"The future of Diesel engines depends on sustainable fuels and the control of harmful emission formation. Up-to-date Diesel engines have complex combustion processes and air-path systems. The latter usually contains a dual loop exhaust gas recirculation system, which exhaust brakes can support. Utilizing the controlling opportunities makes it necessary to develop models for the system. This paper presents a two-state control oriented model. Its inputs are the exhaust gas recirculation valves and the exhaust brake flap positions. Other inputs can be handled as disturbances. These are the engine speed, engine torque, and fuel consumption. The developed model relies on a previously published dual loop exhaust gas recirculation mass flow rate estimator. This estimator needs another input, an intake fresh air mass flow rate or the intake manifold pressure. An important aim was to use only onboard measured parameters. The paper presents the model's equations, the calibration, and the validation, done by the slightly modified interval of the World Harmonized Transient Cycle. At the end of the day, a reproducible model is presented, which, despite the complexity of internal combustion engines, provides a simplified solution for controlling aims.","PeriodicalId":430975,"journal":{"name":"2022 IEEE 1st International Conference on Cognitive Mobility (CogMob)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115867021","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":"An Automated Valet Parking Experiment","authors":"Dániel Doba, Árpád Fehér, Lászlo Szőke","doi":"10.1109/CogMob55547.2022.10117939","DOIUrl":"https://doi.org/10.1109/CogMob55547.2022.10117939","url":null,"abstract":"With the evolution of the automotive industry, professionals' knowledge needs to be broadened, and new methods for their training are required. For this purpose, we present a demonstration vehicle built at the Budapest University of Technology and Economics (BME), together with the solution to the challenging task of automated valet parking. This functionality serves as a baseline that covers most of the needed functionalities in the future autonomous vehicles. In this demo paper we report about the experimental vehicle, path planning and path following, LiDAR-based pedestrian detection and V2X communication that we implemented.","PeriodicalId":430975,"journal":{"name":"2022 IEEE 1st International Conference on Cognitive Mobility (CogMob)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127541012","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}