This paper presents a discrete sliding mode control (DSMC) scheme for a series-series compensated wireless power transfer (WPT) system to achieve fast maximum energy efficiency (MEE) tracking and output voltage regulation. The power transmitter of the adopted WPT system comprises a dc/ac converter, which incorporates the hill-climbing-search-based phase angle control in achieving minimum input current injection from its dc source, thereby attaining minimum input power operation. The power receiver comprises a buck-boost converter that emulates an optimal load value, following the MEE point determined by the DSMC scheme. With this WPT system, no direct communication means is required between the transmitter and the receiver. Therefore, the implementation cost of this system is potentially lower and annoying communication delays, which deteriorate control performance, are absent. Both the simulation and experiment results show that this WPT system displays better dynamic regulation of the output voltage during MEE tracking when it is controlled by DSMC, as compared to that controlled by the conventional discrete proportional-integral (PI) control. Such an improvement prevents the load from sustaining undesirable overshoot/undershoot during transient states.

The first generation of wireless power transfer (WPT) standard Qi, launched in 2010, contains a wide range of transmitter and receiver designs with the aim of maximizing compatibility to attract many manufacturers to share the same standard. Such compatibility feature (i.e., interoperability) has not only attracted over 400 company members in the Wireless Power Consortium (WPC), but also facilitated a fast-growing wireless power market for a decade. The WPC is now expanding the scope of WPT applications to mid-power and high-power applications up to several kilowatts while the Society for Automobile Engineers also set the SAE standard for wireless charging of electric vehicles (EVs) up to tens of kilowatts. Without compromising compatibility, the authors share in this paper their views on the need for a paradigm shift from compatibility to optimal performance in terms of maximum energy efficiency for the entire charging process and minimum charging time. This paradigm change is imminent and important in view of the increasing power of WPT applications. Several enabling technologies essential to the paradigm shift will be addressed.

In this paper, a two-layer ADE algorithm is adopted to monitor the parameters of SS-compensated WPT systems. By only measuring the primary coils voltages and currents, the proposed monitoring method can be applied for multiple-coil SS-compensated WPT systems without any feedback signals from the receivers. Compared to the conventional monitoring method based on the GA, which may find local optimal solutions by the manually tuned parameters, the proposed method based on the two-layer ADE can always find global optimal solutions by the automatically tuned parameters of the differential weight, the crossover rate, and the generations. Experimental results validate that the ADE and the proposed two-layer ADE can monitor the parameters of both two- and three-coil SS-compensated WPT systems more steadily and accurately than the GA. Additionally, the proposed two-layer ADE is verified to monitor the parameters of three-coil SS-compensated WPT systems with three different arrangements more accurately than the ADE.

Maximum energy efficiency tracking (MEET) of series-series (SS)-compensated wireless power transfer (WPT) systems with active rectifiers require the information of mutual coupling coefficient or correlated variables, which are conventionally monitored based on the feedback signals from the receiver to the transmitters via a wireless communication system. In this paper, a very fast hardware-based front-end monitoring strategy is proposed to determine the mutual coupling coefficient of the system within typically 65 ms without any wireless communication system. Compared to existing mathematical model-based methods, the proposed strategy is much faster and more cost-effective by using fewer sensors and simpler equations. The proposed method can therefore be implemented in low-cost digital controllers. Importantly, the parameter values of the transmitter and receiver resonators are not required by the proposed method. Both simulation and experimental results are included to validate the high accuracy and fast speed of the proposed monitoring strategy to monitor the coupling coefficient. Comparative results among the proposed and existing monitoring strategies are also presented.

Conventional control methods for the battery systems of photovoltaic-battery systems in standalone DC microgrids are designed to stringently regulate the bus voltages at the MPP of PV modules while the state-of-charge of the battery is regulated within the tolerances. In this paper, a local hierarchical control is proposed for the battery system to improve the energy efficiency of the entire PV-battery system at the MPP of PV modules while the SOC of the battery is still regulated within the tolerance. Specifically, by allowing the DC bus voltage to deviate within a preset allowable tolerance, the secondary control of the LHC is employed to compute real-time optimal references to its primary control, such that the energy conversion of the entire PV-battery system can be optimized. Simulations exhibit significant efficiency improvement of a 12-PV-battery system under both uniform and nonuniform insolation conditions in a cloudy day and a 600-kW PV-battery system in a sunny day using the proposed LHC. Experiments validate that the energy efficiency of a one-PV-module-battery system controlled by the LHC can be enhanced using shortened sunny- and cloudy-day irradiance profiles for various PV modules. The proposed control scheme can be easily implemented in digital controllers without additional hardware costs.

DC microgrids fed with substantial intermittent renewable energy sources face the immediate problem of power imbalance and the subsequent dc bus voltage fluctuation problem (that can easily breach power system standards). It has recently been demonstrated that dc electric springs (DCES), when connected with series non-critical loads, are capable of stabilizing the voltage of local nodes and improving the power quality of dc microgrids without large energy storage. In this paper, two centralized model predictive control (CMPC) schemes with: 1) non-adaptive weighting factors and 2) adaptive weighting factors are proposed to extend the existing functions of the DCES in the microgrid. The control schemes coordinate the DCES to mitigate the distribution power loss in the dc microgrids, while simultaneously providing their original function of dc bus voltage regulation. Using the DCES model that was previously validated with experiments, simulations based on MATLAB/Simulink platform are conducted to validate the control schemes. The results show that with the proposed CMPC schemes, the DCES are capable of eliminating the bus voltage offsets as well as reducing the distribution power loss of the dc microgrid.