He Yin

Analysis and Tracking of Optimal Load in Wireless Power Transfer Systems

All the wireless power transfer (WPT) systems share a similar configuration including a power source, a coupling system, a rectifying circuit, a power regulating, and charging management circuit and a load. For such a system, both a circuit- and a system-level analyses are important to derive requirements for a high overall system efficiency. Besides, unavoidable uncertainties in a real WPT system require a feedback mechanism to improve the robustness of the performance. Based on the above basic considerations, this paper first provides a detailed analysis on the efficiency of a WPT system at both circuit and system levels. Under a specific mutual inductance between the emitting and receiving coils, an optimal load resistance is shown to exist for a maximum overall system efficiency. Then, a perturbation-and-observation-based tracking system is developed through additional hardware such as a cascaded boost-buck dc-dc converter, an efficiency sensing system, and a controller. Finally, a 13.56-MHz WPT system is demonstrated experimentally to validate the efficiency analysis and the tracking of the optimal load resistances. At a power level of 40 W, the overall efficiency from the power source to the final load is maintained about 70% under various load resistances and relative positions of coils.

Utility Function-Based Real-Time Control of A Battery Ultracapacitor Hybrid Energy System

This paper discusses a utility function-based control of a battery-ultracapacitor (UC) hybrid energy system. The example system employs the battery semiactive topology. In order to represent different performance and requirements of the battery and UC packs, the two packs are modeled as two independent but related agents using the NetLogo environment. Utility functions are designed to describe the respective preferences of battery and UC packs. Then, the control problem is converted to a multiobjective optimization problem solved by using the Karush-Kuhn-Tucker (KKT) conditions. The weights in the objective functions are chosen based on the location of the knee point in the Pareto set. Both the simulation and experimental results show the utility function-based control provides a comparable performance with the ideal average load demand (ALD)-based control, while the exact preknowledge of the future load demand is not required. The utility function-based control is fast enough to be directly implemented in real time. The discussion in this paper gives a starting point and initial results for dealing with more complex hybrid energy systems.

An Adaptive Fuzzy Logic-Based Energy Management Strategy on Battery/Ultracapacitor Hybrid Electric Vehicles

One of the key issues for the development of electric vehicles (EVs) is the requirement of a supervisory energy management strategy, especially for those with hybrid energy storage systems. An adaptive fuzzy logic-based energy management strategy (AFEMS) is proposed in this paper to determine the power split between the battery pack and the ultracapacitor (UC) pack. A fuzzy logic controller is used due to the complex real-time control issue. Furthermore, it does not need the knowledge of the driving cycle ahead of time. The underlying principles of this adaptive fuzzy logic controller are to maximize the system efficiency, to minimize the battery current variation, and to minimize UC state of charge (SOC) difference. NetLogo is used to assess the performance of the proposed method. Compared with other three energy management strategies, the simulation and experimental results show that the proposed AFEMS promises a better comprehensive control performance in terms of the system efficiency, the battery current variation, and differences in the UC SOC, for both congested city driving and highway driving situations.

A Game Theory Approach to Energy Management of An Engine–Generator/Battery/Ultracapacitor Hybrid Energy System

The complex configuration and behavior of multisource hybrid energy systems (HESs) present challenges to their energy management. For a balanced solution, it is especially important to represent and take advantage of the characteristics of each device and the interactive relationship among them. In this paper, multi-agent modeling and a game theory-based control strategy are proposed and combined for the energy management of an example engine-generator/battery/ultracapacitor (UC) HES. The three devices such as engine-generator unit, battery and UC packs are modeled and controlled as independent but related agents, through which the performance and requirements of the individual devices are fully respected. The energy management problem is then formulated as a noncooperative current control (NCC) game. The Nash equilibrium is analytically derived as a balanced solution that compromises the different preferences of the independent devices. The following simulation and experimental results validate the game theory-based control and its real-time implementation. The proposed approach could be further extended to become a general solution for the energy management and control of networked energy systems, in which again fully representing and balancing the different preferences of the components are important.

Equivalent Series Resistance-Based Energy Loss Analysis of a Battery Semiactive Hybrid Energy Storage System

This paper provides a theoretical analysis on the energy loss of a battery-ultracapacitor hybrid energy storage system based on the equivalent series resistances and a pulsed current load profile. The optimal current distribution that minimizes the overall energy loss is proved to be solely determined by the ratio of internal resistances between battery and ultracapacitor packs. Due to a large difference in the internal resistances, a quasi-optimal current distribution can be considered to let the battery pack provide the average load current and ultracapacitor pack supply the entire dynamic load current. This result clearly demonstrates that the ultracapacitor pack should supply the most of the dynamic load current not only because of battery protection, but also for energy loss minimization. Finally, the theoretical analysis is validated by both simulation and experimental results. Additional discussions, such as sensitivity analysis, the influence of the sizing of ultracapacitors, and a realistic test cycle are also added for reference purposes.

Optimization based energy control for battery/super-capacitor hybrid energy storage systems

Batteries have been widely used as electrical energy storage units nowadays. However, due to their low power-density, it is usually necessary to combine batteries with other energy storage units, such as super-capacitors, in hybrid energy systems. In this paper, an optimization based control strategy is proposed to improve the energy efficiency as well as battery life time for battery semi-active hybrid systems. Sharing the similar idea as average current strategy but without any predefined driving cycle, this strategy aims to converge the current of the battery pack to the average current of the test trip by mainly enforcing the energy left in the super-capacitor pack to be same as its initial state while to maintain the current variation as small as possible. To achieve those two objectives, a two-objective optimization problem, whose objectives represents the preferences of the battery and supercapacitor packs, is formed and easily solved by using KKT conditions at any control point. The simulation results of this strategy are compared with those from average current strategy, and show that the proposed strategy can achieve comparable performance.

Quantitative Evaluation of LiFePO

This letter develops a systematic approach to quantitatively evaluate and compare LiFePO4 battery cycle life improvement using ultracapacitors (UCs). The impact of UC sizing on temperature rise, capacity loss, and power fade under a real dynamic load profile is included for a comprehensive discussion and evaluation. It is found that the cycle-related battery capacity losses are reduced by 28.6% (C/3) and 29.0% (1C) using the optimized number of UCs, while the reductions are 36.3% (C/3) and 39.3% (1C) assuming an infinite number of UCs. The reductions on the power fade are 23.6% and 57.3% for the cases with optimized and infinite numbers of UCs, respectively. The reductions on temperature rise, 1.38 °C and 1.93 °C, in the two cases are also observed when discharging from 80% to 30% state of charge in one test cycle. The developed approach in the letter could serve as a general procedure to evaluate the cycle life improvement for other types of batteries when combined with UCs.

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In this paper, the loading effect of a Class E power amplifier (PA) driven 6.78 megahertz (MHz) wireless power transfer (WPT) system is analyzed at both circuit and system levels. A buck converter is introduced and controlled to track an optimal equivalent load that maximizes the system efficiency under uncertainties in the relative position of coils and the final load. For power control, an additional degree of freedom is provided by adding an ultracapacitor bank. A control strategy is proposed to track the maximum efficiency and charge/discharge the ultracapacitor bank through the on/off control of the Class E PA. Thus, high system efficiency can be maintained under various uncertainties and load power demands. Finally, the theoretical analysis and the control scheme are validated in experiments. The results show that the proposed Class E PA-driven MHz WPT system can stably achieve a high efficiency under different coil distances and various constant/pulsed power profiles. The measured highest system efficiency can reach 72.1% at a load power level of 10 W.

Battery Cycle Life Improvement Using Ultracapacitors

One of the key issues for electric vehicle (EV) development is the energy management strategy, especially for those with hybrid energy storage systems. A fuzzy logic based energy management strategy (FEMS) is proposed in this work to determine the power split between two energy storage sources: a battery tank and an ultracapacitor tank. Fuzzy logic control is chosen because of the nonlinearity of the EV plant and real-time control issue. The FEMS is further improved to be adaptive for better control performance. The underlying principle of this adaptive fuzzy logic control is to maximize the system efficiency, to maintain ultracapacitor charge state, and to minimize the battery current variation. NetLogo is used to assess the performance of the proposed methods. Simulation results show that the proposed control method produces better and balanced performance in terms of comparison criteria.

Loading and Power Control for a High-Efficiency Class E PA-Driven Megahertz WPT System

This paper provides quantitative analysis on system efficiency and battery temperature rise in battery-alone system, passive, battery semiactive, and capacitor semiactive hybrid energy storage systems (HESSs). First the system efficiencies and the temperature rises in battery are derived under a pulsed load profile and the four different topologies. Sensitivity analysis is then performed to investigate the influences of the factors (the characteristics of the load profile, the state of charge of battery, and the efficiency of the dc-dc converter) on the four energy storage systems. The proper usage of the HESSs is discussed later based on the results of the sensitivity analysis. It is found that in the most cases the capacitor semiactive HESS is superior in both system efficiency and the suppression of the battery temperature rise. Meanwhile, its behavior is more complicated than that of the battery semiactive HESS. The battery semiactive HESS is suitable for the highly dynamic loads, but its performance more depends on the efficiency of the dc-dc converter. Finally experiments are conducted that validate the previous theoretical discussions.