H.A. Borhan

Publications (3)0 Total impact

• Conference Proceeding: Nonlinear Model Predictive Control for power-split Hybrid Electric Vehicles

  H.A. Borhan, Chen Zhang, A. Vahidi, A.M. Phillips, M.L. Kuang, S. Di Cairano
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  ABSTRACT: In this paper, a causal optimal controller based on Nonlinear Model Predictive Control (NMPC) is developed for a power-split Hybrid Electric Vehicle (HEV). The global fuel minimization problem is converted to a finite horizon optimal control problem with an approximated cost-to-go, using the relationship between the Hamilton-Jacobi-Bellman (HJB) equation and the Pontryagin's minimum principle. A nonlinear MPC framework is employed to solve the problem online. Different methods for tuning the approximated minimum cost-to-go as a design parameter of the MPC are discussed. Simulation results on a validated high-fidelity closed-loop model of a power-split HEV over multiple driving cycles show that with the proposed strategy, the fuel economies are improved noticeably with respect to those of an available controller in the commercial Powertrain System Analysis Toolkit (PSAT) software and a linear time-varying MPC controller previously developed by the authors.
  Decision and Control (CDC), 2010 49th IEEE Conference on; 01/2011
• Conference Proceeding: Model predictive control of a power-split Hybrid Electric Vehicle with combined battery and ultracapacitor energy storage

  H.A. Borhan, A. Vahidi
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  ABSTRACT: In this paper, merits of using an ultracapacitor in combination with a battery in a power-split Hybrid Electric Vehicle (HEV) is analyzed. For this, an online optimization-based model predictive controller (MPC) is designed and a closed-loop model of the system is developed. Based on the definition of C-rate parameter which indicates the discharge intensity of the battery, a number of simulations over standard driving cycles are performed. Closed-loop simulations on a detailed model of the HEV show that adding the ultracapacitor to the ESS unit can reduce intensity of battery discharge, as indicated by the C-rate, noticeably.
  American Control Conference (ACC), 2010; 08/2010
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  Available from: ntnu.no

  Conference Proceeding: Predictive energy management of a power-split hybrid electric vehicle

  H.A. Borhan, A. Vahidi, A.M. Phillips, M.L. Kuang, I.V. Kolmanovsky
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  ABSTRACT: In this paper, a model predictive control (MPC) strategy is developed for the first time to solve the optimal energy management problem of power-split hybrid electric vehicles. A power-split hybrid combines the advantages of series and parallel hybrids by utilizing two electric machines and a combustion engine. Because of its many modes of operation, modeling a power-split configuration is complex and devising a near-optimal power management strategy is quite challenging. To systematically improve the fuel economy of a power-split hybrid, we formulate the power management problem as a nonlinear optimization problem. The nonlinear powertrain model and the constraints are linearized at each sample time and a receding horizon linear MPC strategy is employed to determine the power split ratio based on the updated model. Simulation results over multiple driving cycles indicate better fuel economy over conventional strategies can be achieved. In addition the proposed algorithm is causal and has the potential for real-time implementation.
  American Control Conference, 2009. ACC '09.; 07/2009