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    Wyświetlanie 1-3 z 3
    Tytuł:
    Research on hybrid modeling and predictive energy management for power split hybrid electric vehicle
    Autorzy:
    Wang, Shaohua
    Zhang, Sheng
    Shi, Dehua
    Sun, Xiaoqiang
    Yang, Tao
    Powiązania:
    https://bibliotekanauki.pl/articles/2173576.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    power split HEV
    energy management
    mixed logical dynamical model
    piecewise affine
    model predictive control
    podział mocy
    zarządzanie energią
    silnik hybrydowy
    model dynamiczny
    model mieszany
    model logiczny
    technologia fragmentarycznie pokrewna
    kontrola predykcyjna modelu
    Opis:
    Due to the coexistence of continuity and discreteness, energy management of a multi-mode power split hybrid electric vehicle (HEV) can be considered a typical hybrid system. Therefore, the hybrid system theory is applied to investigate the optimum energy distribution strategy of a power split multi-mode HEV. In order to obtain a unified description of the continuous/discrete dynamics, including both the steady power distribution process and mode switching behaviors, mixed logical dynamical (MLD) modeling is adopted to build the control-oriented model. Moreover, linear piecewise affine (PWA) technology is applied to deal with nonlinear characteristics in MLD modeling. The MLD model is finally obtained through a high level modeling language, i.e. HYSDEL. Based on the MLD model, hybrid model predictive control (HMPC) strategy is proposed, where a mixed integer quadratic programming (MIQP) problem is constructed for optimum power distribution. Simulation studies under different driving cycles demonstrate that the proposed control strategy can have a superior control effect as compared with the rule-based control strategy.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 3; art. no. e137064
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    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
    Tytuł:
    Research on hybrid modeling and predictive energy management for power split hybrid electric vehicle
    Autorzy:
    Wang, Shaohua
    Zhang, Sheng
    Shi, Dehua
    Sun, Xiaoqiang
    Yang, Tao
    Powiązania:
    https://bibliotekanauki.pl/articles/2128153.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    power split HEV
    energy management
    mixed logical dynamical model
    piecewise affine
    model predictive control
    podział mocy
    zarządzanie energią
    silnik hybrydowy
    model dynamiczny
    model mieszany
    model logiczny
    technologia fragmentarycznie pokrewna
    kontrola predykcyjna modelu
    Opis:
    Due to the coexistence of continuity and discreteness, energy management of a multi-mode power split hybrid electric vehicle (HEV) can be considered a typical hybrid system. Therefore, the hybrid system theory is applied to investigate the optimum energy distribution strategy of a power split multi-mode HEV. In order to obtain a unified description of the continuous/discrete dynamics, including both the steady power distribution process and mode switching behaviors, mixed logical dynamical (MLD) modeling is adopted to build the control-oriented model. Moreover, linear piecewise affine (PWA) technology is applied to deal with nonlinear characteristics in MLD modeling. The MLD model is finally obtained through a high level modeling language, i.e. HYSDEL. Based on the MLD model, hybrid model predictive control (HMPC) strategy is proposed, where a mixed integer quadratic programming (MIQP) problem is constructed for optimum power distribution. Simulation studies under different driving cycles demonstrate that the proposed control strategy can have a superior control effect as compared with the rule-based control strategy.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 3; e137064, 1--15
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-3 z 3

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