TY - JOUR AU - Istenes, György AU - Pusztai, Zoltán AU - Kőrös, Péter AU - Horváth, Zoltán AU - Friedler, Ferenc TI - Kriging-Assisted Multi-Objective Optimization Framework for Electric Motors Using Predetermined Driving Strategy JF - ENERGIES J2 - ENERGIES VL - 16 PY - 2023 IS - 12 SN - 1996-1073 DO - 10.3390/en16124713 UR - https://m2.mtmt.hu/api/publication/34018990 ID - 34018990 N1 - Vehicle Industry Research Center, Széchenyi István University, Egyetem Tér 1, Győr, 9026, Hungary Department of Mathematics and Computational Sciences, Széchenyi István University, Egyetem Tér 1, Győr, 9026, Hungary Cited By :1 Export Date: 16 October 2023 Correspondence Address: Friedler, F.; Vehicle Industry Research Center, Egyetem Tér 1, Hungary; email: f.friedler@ga.sze.hu Funding details: European Commission, EC Funding text 1: The research was supported by the European Union within the framework of the National Laboratory for Artificial Intelligence (RRF-2.3.1-21-2022-00004). AB - In this paper, a multi-objective optimization framework for electric motors and its validation is presented. This framework is suitable for the optimization of design variables of electric motors based on a predetermined driving strategy using MATLAB R2019b and Ansys Maxwell 2019 R3 software. The framework is capable of managing a wide range of objective functions due to its modular structure. The optimization can also be easily parallelized and enhanced with surrogate models to reduce the runtime. The framework is validated by manufacturing and measuring the optimized electric motor. The method’s applicability for solving electric motor design problems is demonstrated via the validation process. A test application is also presented, in which the operating points of a predetermined driving strategy provide the input for the optimization. The kriging surrogate model is used in the framework to reduce the runtime. The results of the optimization and the framework’s benefits and drawbacks are discussed through the provided examples, in addition to displaying the properly applicable design processes. The optimization framework provides a ready-to-use tool for optimizing electric motors based on the driving strategy for single- or multi-objective purposes. The applicability of the framework is demonstrated by optimizing the electric motor of a world recorder energy-efficient race vehicle. In this application, the optimization framework achieved a 2% improvement in energy consumption and a 9% increase in speed at a rated DC voltage, allowing the motor to operate at desired working points even with low battery voltage. LA - English DB - MTMT ER - TY - JOUR AU - Pusztai, Zoltán AU - Kőrös, Péter AU - Szauter, Ferenc AU - Friedler, Ferenc TI - Implementation of Optimized Regenerative Braking in Energy Efficient Driving Strategies JF - ENERGIES J2 - ENERGIES VL - 16 PY - 2023 IS - 6 SN - 1996-1073 DO - 10.3390/en16062682 UR - https://m2.mtmt.hu/api/publication/33700166 ID - 33700166 N1 - Cited By :1 Export Date: 16 October 2023 Correspondence Address: Pusztai, Z.; Vehicle Industry Research Center, Hungary; email: pusztai.zoltan@ga.sze.hu Funding details: RRF-2.3.1-21-2022-00002 Funding details: European Commission, EC Funding text 1: The research was supported by the European Union within the framework of the National Laboratory for Autonomous Systems (RRF-2.3.1-21-2022-00002). AB - In this paper, determination of optimized regenerative braking-torque function and application in energy efficient driving strategies is presented. The study investigates a lightweight electric vehicle developed for the Shell Eco-Marathon. The measurement-based simulation model was implemented in the MATLAB/Simulink environment and used to establish the optimization. The optimization of braking-torque function was performed to maximize the recuperated energy. The determined braking-torque function was applied in a driving strategy optimization framework. The extended driving strategy optimization model is suitable for energy consumption minimization in a designated track. The driving strategy optimization was created for the TT Circuit Assen, where the 2022 Shell Eco-Marathon competition was hosted. The extended optimization resulted in a 2.97% improvement in energy consumption when compared to the result previously achieved, which shows the feasibility of the proposed methodology and optimization model. LA - English DB - MTMT ER - TY - CHAP AU - Kőrös, Péter ED - Szauter, Ferenc ED - Csikor, Dániel ED - Földesi, Rita ED - Suta, Alex ED - Szabó, Amanda TI - A 2022-es Shell Eco-marathon verseny értékelése és fejlesztési irányok meghatározása T2 - Mobilitás és környezet JÖVŐFORMÁLÓ JÁRMŰIPARI KUTATÁSOK Konferenciakiadvány 2022. novemberi konferencia PB - Széchenyi István Egyetem CY - Győr SN - 9786156443182 PY - 2022 SP - 91 EP - 109 PG - 19 UR - https://m2.mtmt.hu/api/publication/34132508 ID - 34132508 LA - Hungarian DB - MTMT ER - TY - CHAP AU - Fersztl, Barnabás AU - Pusztai, Zoltán AU - Kőrös, Péter ED - Szauter, Ferenc ED - Csikor, Dániel ED - Földesi, Rita ED - Suta, Alex TI - Görgős mérőrendszer tervezése alacsony teljesítményű hajtásláncok komplex vizsgálatához T2 - „Digitális Járműipari Kutatások a Széchenyi István Egyetemen – Mesterséges Intelligencia a mobilitásban” Konferenciakiadvány 2022. június PB - Széchenyi István Egyetem CY - Győr SN - 9786156443151 PY - 2022 SP - 136 EP - 143 PG - 8 UR - https://m2.mtmt.hu/api/publication/34032719 ID - 34032719 LA - Hungarian DB - MTMT ER - TY - CHAP AU - Kecskeméti, István AU - Kőrös, Péter AU - Unger, Miklós ED - Szauter, Ferenc ED - Csikor, Dániel ED - Földesi, Rita ED - Suta, Alex TI - Autonóm funkciók implementálása energiahatékony versenyjárműbe T2 - „Digitális Járműipari Kutatások a Széchenyi István Egyetemen – Mesterséges Intelligencia a mobilitásban” Konferenciakiadvány 2022. június PB - Széchenyi István Egyetem CY - Győr SN - 9786156443151 PY - 2022 SP - 36 EP - 42 PG - 7 UR - https://m2.mtmt.hu/api/publication/34032240 ID - 34032240 LA - Hungarian DB - MTMT ER - TY - GEN AU - Pusztai, Zoltán AU - Kőrös, Péter AU - Friedler, Ferenc TI - Modelling Steering Resistance to Save Energy PY - 2022 UR - https://m2.mtmt.hu/api/publication/33082589 ID - 33082589 N1 - Előadás LA - English DB - MTMT ER - TY - JOUR AU - Pusztai, Zoltán AU - Kőrös, Péter AU - Szauter, Ferenc AU - Friedler, Ferenc TI - Regenerative Braking Optimization of Lightweight Vehicle based on Vehicle Model JF - CHEMICAL ENGINEERING TRANSACTIONS J2 - CHEM ENG TR VL - 94 PY - 2022 SP - 601 EP - 606 PG - 6 SN - 1974-9791 DO - 10.3303/CET2294100 UR - https://m2.mtmt.hu/api/publication/33081407 ID - 33081407 N1 - Cited By :1 Export Date: 16 October 2023 Correspondence Address: Pusztai, Z.; Széchenyi István University, Egyetem tér 1, Hungary; email: pusztai.zoltan@ga.sze.hu Funding details: RRF-2.3.1-21-2022-00004 Funding details: Nemzeti Kutatási, Fejlesztési és Innovaciós Alap, NKFIA Funding text 1: Project no. TKP2021-NKTA-48 has been implemented with the support provided by the Ministry of Innovation and Technology of Hungary from the National Research, Development and Innovation Fund and the Artificial Intelligence National Laboratory Program, RRF-2.3.1-21-2022-00004. LA - English DB - MTMT ER - TY - JOUR AU - Pusztai, Zoltán AU - Kőrös, Péter AU - Friedler, Ferenc TI - Modelling Steering Resistance to Save Energy JF - IOP CONFERENCE SERIES: MATERIALS SCIENCE AND ENGINEERING J2 - IOP CONF SER MATER SCI ENG VL - 1237 PY - 2022 IS - 1 SP - 012016 SN - 1757-8981 DO - 10.1088/1757-899X/1237/1/012016 UR - https://m2.mtmt.hu/api/publication/32895400 ID - 32895400 LA - English DB - MTMT ER - TY - JOUR AU - Pusztai, Zoltán AU - Kőrös, Péter AU - Szauter, Ferenc AU - Friedler, Ferenc TI - Vehicle Model-Based Driving Strategy Optimization for Lightweight Vehicle JF - ENERGIES J2 - ENERGIES VL - 15 PY - 2022 IS - 10 SN - 1996-1073 DO - 10.3390/en15103631 UR - https://m2.mtmt.hu/api/publication/32829186 ID - 32829186 N1 - Cited By :9 Export Date: 16 October 2023 Correspondence Address: Pusztai, Z.; Vehicle Industry Research Center, Egyetem tér 1, Hungary; email: pusztai.zoltan@ga.sze.hu Funding details: Nemzeti Kutatási, Fejlesztési és Innovaciós Alap, NKFIA Funding text 1: Project no. TKP2021-NKTA-48 has been implemented with the support provided by the Ministry of Innovation and Technology of Hungary from the National Research, Development and Innovation Fund, financed under the TKP2021-NKTA funding scheme. Members of the SZEnergy Team (https://szenergy.hu/) provided internal telemetry data, images, and support during the field test, which the authors gratefully acknowledge. LA - English DB - MTMT ER - TY - CHAP AU - Krecht, Rudolf AU - Pusztai, Zoltán AU - Kőrös, Péter ED - Péter, Tamás TI - Modulrendszerű, önvezérlésre alkalmas, távvezérelhető, könnyű páncélvédettségű félplatós terepjáró katonai és katasztrófavédelmi célú terepjáró bázisjármű és kapcsolódó cserefelépítmények fejlesztése T2 - XV. IFFK 2021: Innováció és fenntartható felszíni közlekedés PB - Magyar Mérnökakadémia (MMA) CY - Budapest SN - 9789638887559 PY - 2021 SP - 21 UR - https://m2.mtmt.hu/api/publication/32778282 ID - 32778282 LA - Hungarian DB - MTMT ER -