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Compared to the doubly fed machine, the brushless doubly fed machine (BDFM) has high reliability and low maintenance requirements. First, by taking the negative conjugation of the control motor variables in rotor reference frame, a state-space model of BDFM is derived. It is then transformed into synchronous reference frame, called synchronous reference frame state-space model (SSSM). In this way, all the variables of the SSSM are DC under the static state. Second, on the basis of the analysis of static equations, the possible output torque limits are obtained. Third, the causes of losing control are analyzed by the flux and the torque derivatives. A new control strategy called synthetic vector direct torque control (SVDTC) is proposed to solve the losing control problems of the conventional direct torque control (DTC). Finally, the correctness of the results of this paper is verified by calculation examples and simulation results, the losing control problems can be solved, and the theoretical output capacity limits can be reached using SVDTC.

An energy management strategy (EMS) considering both optimality and real-time performance has become a challenge for the development of hybrid electric vehicles (HEVs) in recent years. Previous EMSes based on the optimal control theory minimize the fuel consumption, but cannot be directly implemented in real-time because of the requirement for a prior knowledge of the entire driving cycle. This paper presents an innovative design concept and method to obtain a power management strategy for HEVs, which is independent of future driving conditions. A quadratic performance index is designed to ensure the vehicle drivability, maintain the battery energy sustainability and average and smooth the engine power and motor power to indirectly reduce fuel consumption. To further improve the fuel economy, two rules are adopted to avoid the inefficient engine operation by switching control modes between the electric and hybrid modes according to the required driving power. The derived power of the engine and motor are related to current vehicle velocity and battery residual energy, as well as their desired values. The simulation results over different driving cycles in Advanced Vehicle Simulator (ADVISOR) show that the proposed strategy can significantly improve the fuel economy, which is very close to the optimal strategy based on Pontryagin's minimum principle.

This paper presents a novel decoupling control strategy, corresponding to the vector control of induction motors, for the Brushless Doubly-Fed Machine (BDFM). The affine nonlinear state equation of the BDFM within an arbitrary rotating reference frame is also given for the first time. To achieve decoupling control over torque and flux, an input-output feedback linearization control strategy is used. A new control arithmetic, realized in the synchronous reference frame oriented by the control motor rotor flux, is developed. The necessary condition for implementation of the proposed control strategy is demonstrated. Simulation results confirm the feasibility and superb performance of the proposed strategy.

This paper presents a single-degree-of-freedom energy optimization strategy to solve the energy management problem existing in power-split hybrid electric vehicles (HEVs). The proposed strategy is based on a quadratic performance index, which is innovatively designed to simultaneously restrict the fluctuation of battery state of charge (SOC) and reduce fuel consumption. An extended quadratic optimal control problem is formulated by approximating the fuel consumption rate as a quadratic polynomial of engine power. The approximated optimal control law is obtained by utilizing the solution properties of the Riccati equation and adjoint equation. It is easy to implement in real-time and the engineering significance is explained in details. In order to validate the effectiveness of the proposed strategy, the forward-facing vehicle simulation model is established based on the ADVISOR software (Version 2002, National Renewable Energy Laboratory, Golden, CO, USA). The simulation results show that there is only a little fuel consumption difference between the proposed strategy and the Pontryagin's minimum principle (PMP)-based global optimal strategy, and the proposed strategy also exhibits good adaptability under different initial battery SOC, cargo mass and road slope conditions.

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Hybrid Electric Vehicles(HEV) are usually powered by two different energy sources, typically, they are equipped with an internal combustion engine and a bank of batteries. It is important to split the required power between the two energy sources in order to minimize fuel consumption. In this paper, this problem is posed as an optimal control problem and solved using improved Dynamic Programming (DP), improved DP is applied to reduce the computing time, Finally, it is simulated based on PSATv6.1, compared with other algorithm, the results of simulation indicate that the fuel economy of series HEV is improved greatly.

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