Abstract
In this paper, a land and air vehicle equipped with hybrid power unit with turboshaft engine was introduced, and a velocity prediction-based model predictive control (VPMPC) for the energy management strategy (EMS) was proposed for the vehicle. Firstly, based on the experiment data, the modeling approach based on data driven method was adopted to obtain the mathematical model of turboshaft engine. Besides, the models of generator, battery, motors were established. The deep learning method was adopted to design power predictor by training with random integrated driving cycles to improve the accuracy of the prediction model for the model predictive control (MPC). Subsequently, the EMS based on MPC using the power predictor was introduced to regulate the state of charge of battery and the exhaust gas temperature of turboshaft engine. The compared simulation results of different weight coefficients for proposed EMS were also discussed. The simulation results showed the high accuracy of mathematical model of turboshaft engine, and the effectiveness of the proposed EMS is demonstrated.
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Wei, Z., Ma, Y., Xiang, C., Liu, D. (2021). Velocity Prediction Based Model Predictive Control for Energy Management in Land and Air Vehicle with Turboshaft Engine. In: Li, K., Coombs, T., He, J., Tian, Y., Niu, Q., Yang, Z. (eds) Recent Advances in Sustainable Energy and Intelligent Systems. LSMS ICSEE 2021 2021. Communications in Computer and Information Science, vol 1468. Springer, Singapore. https://doi.org/10.1007/978-981-16-7210-1_25
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DOI: https://doi.org/10.1007/978-981-16-7210-1_25
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