This paper proposes a two-layer structure Internet-distributed energy management strategy (ID-EMS) for connected plug-in hybrid electric vehicles (PHEVs) to deal with two significant challenges in the real-time global optimization process. One is that the traffic flow information from the commercial intelligent transportation system (ITS) is insufficient to accurately predict future driving conditions, which is alleviated by introducing the computer vision-based detection method for traffic flow density. The other is the conflict between global optimality and real-time capability, which the algorithm complexity analysis solves. Namely, the maximum problem size of the global optimization under a given computing power is derived to ensure real-time capability. Finally, an Internet-distributed vehicle-in-the-loop (ID-VIL) simulation platform is introduced to evaluate the proposed ID-EMS’s feasibility through an on-road driving experiment. Some extreme conditions, such as heavy calculation load and network failure, are also tested.

By introducing the concept of “data coupling” into the existing Hardware-In-the-Loop (HIL) for Hybrid Electric Vehicles (HEVs), several distributed subsystems are now able to be coupled together to constitute an Internet-Distributed Vehicle-In-the-Loop (ID-VIL) simulation platform. These subsystems include: the cloud server (Cloud) which acts as the central control node, the Electric Vehicle (EV) which serves as the Vehicle-In-the-Loop (VIL), and the HIL simulation platforms for engine (EIL) and battery (BIL). The proposed ID-VIL configuration makes it possible that the EV which doesn't contain any hybrid powertrain can simulate the output of a HEV's power system, meanwhile the subsystems of HEV (such as engine and battery) which are actually deployed on HIL platforms can work just the same as on board. The feasibility and reliability of ID-VIL system are verified by a 10 seconds acceleration test, a 7 kilometers urban road tests and the transparency analysis of the test result.

Dynamic wireless power transfer (DWPT) can solve the limitation of battery capacity of electric vehicles, and has a good application prospect. In order to solve the problem of weak coupling power supply in a DWPT system with segmented coil mode, an improved real-time strong coupling coil arrangement mode is proposed in this paper. First, the characteristics of the typical coil arrangement mode is analyzed by establishing a DWPT model, in which the mutual inductance decreases sharply in a certain range. In order to ensure the stability of mutual inductance, an improved long receiving coil arrangement mode is proposed, and its advantage of the low coil cost is analyzed theoretically. Further, the optimal process of the improved coil mode is designed based on the genetic algorithm, and an application case of the electric bus is given. Finally, the feasibility of the coil design process is verified by simulation, and the performance advantages of the proposed scheme are verified by a 30 kW WPT platform.

As a technology that makes power transfer more flexible, wireless power transfer (WPT) technology has become a hot research topic in recent years. However, most of the existing studies are based on a DC–DC WPT system. If applied to AC loads, the traditional system usually contains multiple energy conversion stages, which lead to a low transmission efficiency and therefore higher costs. Besides, the necessary large electrolytic capacitors make the system unreliable and bulky. The goal of this study is to design a reliable and efficient WPT system featuring constant current (CC) and constant voltage (CV) output for AC loads. In this work, an inductor–capacitor–capacitor series (LCC–S) enveloped modulation wireless power transfer (EM–WPT) system is proposed. The design of the proposed system is elaborated in this paper, including the working principle of the system’s power converters, the relationship between CC/CV output characteristics and the input current, and the control strategy of CC/CV output based on an AC–AC boost converter. Lastly, an experimental prototype is configured to verify the CC/CV characteristics. The measured overall efficiency of the system reaches 91% and the power factor of input power supply approaches 1.

The distribution network (DN) reconfiguration is a well-known optimal power flow (OPF) problem. However, with the transition of DN from “passive” to “active”, new technical challenges arise in DN reconfiguration. This paper addresses two key issues in this regard. Firstly, the integration of local renewable generation (LRG) introduces uncertainty into the system-wide power flow of the DN. Secondly, the coupling between DN and the external power grid (EPG) affects the determination of DN root voltage. Consequently, a novel DN reconfiguration approach is proposed in this paper. To begin with, an explicit mixed-integer convex OPF model is constructed that incorporates both the EPG and DN sides. Notably, the OPF model embeds the function of local droop control that is provided by LRG. Subsequently, the original OPF model is decomposed, and the distributed optimization methods based on the augmented Lagrangian relaxation are employed. The paper comprehensively discusses parallel processing and asynchronous implementation as parts of the distributed optimization procedure. Furthermore, to address the uncertainty related to LRG integration, the extreme scenario method is used to provide a robust decision regarding DN reconfiguration. The application of the extreme scenario method in the distributed OPF model concerning DN reconfiguration is successively developed. Finally, numerical results are presented to demonstrate the acceptable performance of the distributed optimization methods, in terms of optimality and convergence. Also, these are validated that the proposed DN reconfiguration approach exhibits robustness to LRG integration, the system-wide voltage profile is improved, and the active power loss is effectively reduced using the proposed DN reconfiguration approach.

This paper proposes a scheme that can compensate for the nonlinear characteristics of voltage source inverters (VSIs) for low-voltage delta-connected induction motors (IMs). Due to the nonlinearity introduced by the dead-time, the on/off delay, and the voltage drop across the power device, the output voltage of VSIs is seriously distorted, causing distortion in the phase current of the IM, which will lead to output torque ripple. However, the existing compensation methods for three-phase VSIs are derived from star-connected loads, or ignore the conducting properties of power devices. Moreover, the current polarity detection near the current zero is quite complex. In this paper, by taking such nonlinear characteristics into consideration, especially the conducting property of metal-oxide-semiconductor field effect transistors (MOSFETs), an output voltage model of VSIs for low-voltage delta-connected induction motors is presented. After that, in view of the difficulty in detecting the line current polarity near the current zero which might lead to the wrong compensation, an advancing current crossing zero (ACCZ) compensation is proposed. Subsequently, a compensation scheme which combines the compensation based on the VSI output voltage model and ACCZ compensation is proposed. Finally, the proposed compensation scheme is implemented based on a digital signal processor (DSP) drive system. The experimental results show that the proposed scheme has better performance than the common method in terms of suppressing the effect of the nonlinear characteristics of VSI, which demonstrates that the proposed compensation scheme is feasible and effective for the compensation of the nonlinear characteristics of VSI for low-voltage delta-connected IMs.