Energy management strategies play an important role in performance optimization of plug-in hybrid electric vehicles (PHEVs), and can be further improved by incorporating external traffic information. Motivated by this, an adaptive equivalent consumption minimization strategy considering traffic information is proposed in this study to facilitate the effective energy management of PHEVs. First, the initial equivalent factors in terms of different initial state of charge (SOC) and driving distance are searched by genetic algorithm. Then, the simplified dynamic programming is leveraged to determine the optimal SOC trajectory according to the traffic information with fast calculation speed. The fuzzy controller is employed to regulate the equivalent factor dynamically, thus enabling effective tracking of the reference SOC trajectory. A hardware-in-the-loop simulation platform based on the virtual scene is developed to validate the performance of controller. Simulation and experimental results highlight that the proposed strategy can lead to less fuel consumption, compared to traditional equivalent consumption minimization strategy, thereby proving its feasibility.

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Nowadays, the development of electric vehicle equipped with a two-speed automatic transmission has become a hotspot. As well known, the automatic transmission operates with power loss including gear meshing loss, bearing loss, and oil churning loss. This paper focuses on the bulk temperature prediction of a two-speed automatic transmission using thermal network method. An integrated model, including an efficiency model and a heat balance model, is proposed, which makes it possible to predict power loss, bulk temperature, and temperature distributions under different conditions. In the efficiency model, each part of power losses from gear meshes is studied to calculate the summation of mechanical power losses in the transmission, including losses of gear meshing, bearing and oil churning. In the heat balance model, the entire gearbox is divided into elements with a uniform temperature connected by thermal resistances which account for conduction, convection, and radiation, based upon the first law of thermodynamics for transient conditions. The effectiveness of bulk temperature prediction using thermal network method is validated by the comparison between simulation results and the experimental data. Consequently, this study on heat transfer characteristics, thermal characteristics, and bulk temperature prediction of the two-speed automatic transmission has significant academic and application values.

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Impedance analysis has been widely used in small-signal stability analysis of power systems and power electronic device. This study proposes an iterative approach to impedance model of individual device. The proposed method applies numerical iteration in the calculation of impedance model instead of complex mathematical derivation. It is easy to be implemented in computer programs. First, initial value of a key impedance/admittance of the target device is set. Second, an iterative algorithm is designed according to structure of the device and transfer functions of its components. Finally, the equivalent impedance is computed and stability characteristics of the whole system are analysed. The obtained model could include all elements of the target device, such as phase-locked loop and shaft system. Thus, it could also be applied to the analysis of sub-synchronous control interaction and torsional interaction. The proposed method could provide impedance contribution from different parts of the target device. This character will benefit the analysis and solution of system instability.