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Wyszukujesz frazę "vehicle drive energy management" wg kryterium: Temat

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    Tytuł:
    Cooperation of a PEM fuel cell and a NiMH battery at various states of its charge in a FCHEV drive
    Autorzy:
    Pielecha, Ireneusz
    Szwajca, Filip
    Powiązania:
    https://bibliotekanauki.pl/articles/2038208.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
    Tematy:
    hybrid drive
    fuel cells
    energy flow
    vehicle drive energy management
    Opis:
    The development of electromobility is focused on the design and implementation of increasingly more effective electric drives. In such a system, apart from energy recovery, it is not possible to recharge the batteries while driving. Electric vehicles equipped with fuel cells and a battery (FCHEV – fuel cell hybrid electric vehicle) in a parallel configuration boast increased energy transfer capabilities. The article presents an energy flow analysis in a parallel hybrid drive system with fuel cells and a battery. The research was carried out on a 30 W vehicle made in 1:10 scale with a NiMH battery and a fuel cell with a proton exchange membrane (PEM). Increasing driving dynamics causes a 29% increase in energy consumption, 43.6% reduction of energy transfer from a fuel cell and a 23% increase of in the energy share intended for battery charging. Continuous operation of the system in full power mode ensures a much greater efficiency of energy transmission to the drive train (95%) compared to the system operating in dynamic driving conditions – 64–75%.
    Źródło:
    Eksploatacja i Niezawodność; 2021, 23, 3; 468-475
    1507-2711
    Pojawia się w:
    Eksploatacja i Niezawodność
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Driving energy management of front-and-rear-motor-drive electric vehicle based on hybrid radial basis function
    Autorzy:
    Sun, Binbin
    Zhang, Tiezhu
    Ge, Wenqing
    Tan, Cao
    Gao, Song
    Powiązania:
    https://bibliotekanauki.pl/articles/224152.pdf
    Data publikacji:
    2019
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    electric vehicle
    drive
    energy management
    optimization
    torque distribution
    predictive model
    hardware test
    pojazd elektryczny
    napęd
    zarządzanie energią
    optymalizacja
    moment obrotowy
    model predykcyjny
    Opis:
    This paper presents mathematical methods to develop a high-efficiency and real-time driving energy management for a front-and-rear-motor-drive electric vehicle (FRMDEV), which is equipped with an induction motor (IM) and a permanent magnet synchronous motor (PMSM). First of all, in order to develop motor-loss models for energy optimization, database of with three factors, which are speed, torque and temperature, was created to characterize motor operation based on HALTON sequence method. The response surface model of motor loss, as the function of the motor-operation database, was developed with the use of Gauss radial basis function (RBF). The accuracy of the motor-loss model was verified according to statistical analysis. Then, in order to create a two-factor energy management strategy, the modification models of the torque required by driver (Td) and the torque distribution coefficient (β) were constructed based on the state of charge (SOC) of battery and the motor temperature, respectively. According to the motor-loss models, the fitness function for optimization was designed, where the influence of the non-work on system consumption was analyzed and calculated. The optimal β was confirmed with the use of the off-line particle swarm optimization (PSO). Moreover, to achieve both high accuracy and real-time performance under random vehicle operation, the predictive model of the optimal β was developed based on the hybrid RBF. The modeling and predictive accuracies of the predictive model were analyzed and verified. Finally, a hardware-in-loop (HIL) test platform was developed and the predictive model was tested. Test results show that, the developed predictive model of β based on hybrid RBF can achieve both real-time and economic performances, which is applicable to engineering application. More importantly, in comparison with the original torque distribution based on rule algorithm, the torque distribution based on hybrid RBF is able to reduce driving energy consumption by 9.51% under urban cycle.
    Źródło:
    Archives of Transport; 2019, 49, 1; 47-58
    0866-9546
    2300-8830
    Pojawia się w:
    Archives of Transport
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-2 z 2

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