The application of the multi-coil or coil array, which enhances the freedom of power transfer, is an important topic in Megahertz Wireless Power Transfer (MHz WPT). The most typical and straightforward approach for driving multiple coils is to use the same number of power amplifiers (PAs), with each coil driven by a separate PA. A more efficient and simplified solution is to use a single PA to drive multiple coils or a coil array simultaneously, which significantly reduces the number of required PAs, thereby simplifying the overall system complexity and lowering costs. This work provides a method that uses a Class D PA and a Zero Voltage Switching (ZVS) tank, together with properly designed impedance matching networks, to realize the driving of multiple coils using a single PA. The soft switching, the gain design, and the influence of the mutual inductance between coils are all taken into consideration. A 6.78 MHz WPT system with a GaN-based Class D PA driving two coils arranged in a Double-D-like structure is implemented. The system supports arbitrary placement, number, and the power level of the receiving sides. The peak efficiency of 88.7% is achieved with a total output power of approximately 200W. The experimental results validate the proposed multi-coil driving method and demonstrate its potential for multi-coil MHz WPT applications.

Multivariate time series forecasting is critical for industrial applications such as predictive maintenance and anomaly detection. However, existing Transformer-based models often struggle to capture short-term residual patterns and are vulnerable to noise due to their uniform treatment of attention heads and lack of adaptability to input dynamics. To address these challenges, we propose the Residual Aggregation and Multi-Head Attention Reweighting Autoformer (RAMAR), an enhanced Autoformer-based architecture tailored for complex industrial environments. RAMAR introduces two complementary modules: the Local Residual Aggregator (LRA), which refines high-frequency residuals via bottleneck convolutions and gated fusion, and the Dynamic Head Reweighting Module (DHRM), which calibrates attention heads using multi-scale temporal–channel convolutions to suppress noisy activations and emphasize informative signals. Extensive experiments on three public ETT datasets demonstrate that RAMAR consistently outperforms strong baselines across multiple evaluation metrics, confirming its robustness and effectiveness for real-world industrial forecasting.

Rapidly developing household energy storage systems raise the demand for corresponding DC-DC converters. Although topologies like LLC have already achieved good performance in these large-power and wide-voltage-range applications, they still have shortcomings in dealing with low-voltage battery cells. When converting from low voltage to high voltage, conventional methods can hardly control output current well when the normalized voltage gain is greater than one. Moreover, they cannot ensure a constantly small turn-off current on the low-voltage side over various working conditions, which affects efficiency and stability. To overcome these drawbacks, the paper proposes a hybrid strategy combining frequency and phase modulation for LC resonant converters. First, the theoretical model of the proposed method is constructed and analyzed. Second, a circuit is built and the proposed method is implemented, which is subsequently tested at different working conditions. As the experimental result, the actual output current is close to the expectation and the turn-off current is nearly a small constant at all the working conditions. Hence, the proposed modulation strategy is verified to solve those drawbacks. Furthermore, based on this method, close-loop output current and voltage controller will also be easier to design.

The continuous-control-set model predictive control (CCS-MPC) has been proven as a suitable multi-input multi-output (MIMO) control method for the Multi-Active-Bridge (MAB) converter. It can improve the dynamic response, minimize the cross-coupling effect inherently, and simplify the controller design. However, the constraints on the phase shift angle of the MAB converter are inevitable and have not been addressed in the existing CCS-MPC scheme. To overcome this issue, this paper proposed a CCS-MPC method for MAB converter that considers the phase shift constraints. The optimization problem is formulated based on the predictive model and then converted to a standard quadratic programming (QP) problem with phase shift constraints. The optimization package OSQP is employed for solving the constrained QP problem. The effectiveness of the proposed control method is validated through simulation and experiment.

Traditionally, the theoretical model of a coil is considered to be an ideal inductance in series with a resistor. The ability of a coil in a wireless power transfer (WPT) system to transfer power wirelessly is assessed by the Q value, which is the ratio between the imaginary part and the real part of the input impedance, describing the relationship between the amount of power transferred and the power loss. However, as the working frequency increases, the traditional model does not seem to fit the impedance characteristic well. In this work, the theory of one-port black-box circuit and the traditional coil model are firstly discussed and then a novel model based on the equivalent parasitic capacitor of the port is proposed to describe the behaviors of a coil. Based on the new model introduced, two new parameters are defined to suggest the power transfer ability. Two experiments are conducted. One of the experiments investigates the electric characteristic of the coil and another one understands its magnetic characteristic. Both experiments suggest the reasonability of the new model.

Multi-Active-Bridge (MAB) converter has complex power flow control requirements, which can be tackled by the continuous-control-set model predictive control (CCS-MPC) method. This controller has a simple and extensible design procedure, exhibiting excellent dynamic performance and in-tuitive parameters, without requiring decoupling consideration. However, the inevitable digital delay can reduce the phase margin and negatively impact its dynamic performance. To overcome this issue, this paper introduces a delay compensation mechanism that alters the execution sequence of control actions. The modified system model, predictive law, and control law under this mechanism are derived. The effectiveness of this method is validated by simulation. The influence of weighting factors is also analyzed to present a controller design guidance.

The papers in this special section focuses on the development of modeling the charging loads and behaviors of electric vehicles (EVs) and on the novel control methods for navigating and charging/discharging EVs. Due to the energy demand growth and environmental concerns, EVs have received a prominent interest by academia, industry, and government. This has attracted in recent years the study on the integration of EVs in the market. To make this integration widespread, several challenges need to be addressed and various shortcomings require solutions.

As the renewable power sources increase their penetration in power systems, the proper schedule and control for battery storage systems have become an urgent problem. In this paper, we proposed a new system framework for multi-port energy router-based battery pack active balance system. Three ports of the energy router are serially connected so that the power can flow among each battery pack to balance state of charge. Besides, the power level of the system is expanded due to this topology. A hierarchical power schedule strategy is proposed to form a comprehensive energy management in schedule layer, control layer, and driver layer. Simulation results show the effectiveness of the proposed framework and control strategy.

With the development of technology in modern society, more and more electrical and electronic instruments has been invented and used in factories and our daily life. Power supply is the basic and important need of any electrical and electronic appliance, but energy storage technologies for mobile use is far from satisfactory. For instance, one of the most important performance of Electric Vehicle(EV) is the range ability. Because of the constraints of battery capacity and charging consumes a long period of time, range anxiety is the fatal shortcoming of EV.Wireless power transfer(WPT) technology could alleviate the shortcoming of range anxiety to a large extent. With the WPT system’ spread, the charging process could be happening wherever and whenever the EV is parked.In the research area of WPT system, circuits design, coil design, compensation topology and control methods are the four most important parts. Improving the power transfer capacity(including power capacity and the range of transfer distance), system’s reliability and efficiency of the system are the main purposes of this research. By applying medium-frequency and optimized coil design as well as specially designed control strategy, a medium-frequency high-power WPT system is realized.

Multi-port AC-coupled converter (MAC) is promising to become the next-generation energy router in future Micro-grid and energy Internet to satisfy the upcoming requirement. As the most critical component of MAC, the multi-winding transformer needs a suitable model to achieve power flow analysis and flexible control. This paper analyzes the multi-winding transformer model suitable for MAC application. Three existing transformer modeling methods have been investigated, i.e. self-/mutual-inductance matrix, extended T model, and extended cantilever model. Their equivalent conversions to the expected model have been derived. A four-port multi-winding transformer is designed for the Multi-Active-Bridge converter. The experiment and simulations are performed to compare the advantages and disadvantages of three transformer models.

This article proposes a charging management of electric vehicles (EVs) that considers time anxieties and different behaviors of EV customers. The time anxiety concept is newly presented to address some uncertain events that may happen meanwhile charging of EVs, affect their charging patterns, and prevent them from meeting their energy demands. The working principle of the concept relies on prioritizing the charging before the event occurrences, and thus changing the EV charging patterns. Based on this concept, four different EV customer behaviors are proposed and their influences are investigated. The EV charging problem is formulated as a generalized nash equilibrium (NE) game, in which each EV minimizes its charging cost given its charging requirements and the charging facility constraints. The solution is developed on the basis of receding horizon optimization and reached iteratively in a distributed manner. Detailed simulation and comparison results are introduced to verify the effectiveness of the proposed charging management with the different time-anxiety-based EV customer behaviors.

Charging station that incorporates renewable energy resource and energy storage is a promising solution to meet the growing charging demand of electric vehicles (EVs) without the need to expand the distribution network. The aggregation of multiple energy resources and EVs requires an efficient and flexible energy management strategy. This article presents a two-stage scheme to solve the power allocation and charging coordination of plugged-in EVs. Game-theory-based control is utilized to address the interaction among different components for respecting their individual preferences. The first stage determines the power allocation of photovoltaic, battery, and the grid as well as total charging power for EVs. In the second stage, charging power dispatch among individual EVs is coordinated based on the available total charging power determined in the first stage. As a result, the two energy management problems of charging station are addressed sequentially. The proposed solution is validated via simulation and experiment, and the comparisons with benchmarks show its advantages.

User behavior has attracted growing attention recent years in electric vehicles (EVs) charging coordination problems. This paper proposes a spatial EV fleet charging coordination system considering charging station distribution and user behavior. Firstly, the configuration of the coordination system is introduced and private information protection is highlighted in this system. Traffic uncertainty model, charging station charging pole schedule algorithm (CPSA) and EV mobility model are designed to reflect the spatial interaction of the system. Then, an user behavior based EV coordination algorithm is proposed to maximize upcoming EV user's satisfaction level. Detailed simulation results are presented to verify the effectiveness of proposed EV coordination system. It shows that this system increases EV user's satisfaction level in charging coordination process and spatially shifts the overload of charging stations.

There are 2 wireless power standards for the mobile device market: Qi standard and AirFuel standard with frequencies of hundreds of kHz and 6.78 MHz. This paper presents a dual-band wireless transmitter operating at both 200 kHz and 6.78 MHz. A dual-band reconfigurable PA with Class E and half-bridge modes is introduced to decrease the size of transmitter. Meanwhile, the eddy current loss model of parallel connected dual-band coils is established to provide guidance for coil design. Finally, a dual-band charging pad with specially designed "decoupling ring" is proposed, which can effectively reduce the extra loss of dual-band operation.

Wireless power transfer (WPT) operating at megahertz (MHz) frequency, i.e., MHz WPT, is favorable for its compact and light circuit component and higher special freedom (longer transfer distance). This paper proposes a Class E active rectifier for MHz WPT applications. The active rectifier is consist of a ac inductor (the receiving coil), a resonant capacitor, an active switch (MOSFET) and a filter capacitor. The duty cycle of the switch can be controlled to achieve output voltage regulation. Voltage and current waveforms of the active rectifier as well as the relationship between output voltage and switch duty cycle are derived. Proposed derivation and analysis are well verified in the simulation platform and real experiments. The proposed active rectifier is favorable for its concise circuit topology and can be widely used in the consumer electronic devices applications.

With the widespread of consumer electronics, household appliances and electric vehicle (EV), the household energy consumption is gradually increasing. To reduce the burden of distribution grid and meet the growing energy demand, photovoltaic (PV) panels and energy storage could be introduced and deployed at home. Thus, the home energy system is gradually becoming an integrated multiple energy system including the distribution grid, PV panels, battery energy storage, EV and home loads. An efficient energy management is important for the integrated energy system to save cost and comprehensively utilize their distinct characteristics. In this paper, the energy management problem is formulated to minimize the daily electricity purchase cost. The dual attributes of EV, i.e. energy storage and mobility, are both considered in the problem. The numerical result demonstrates that the energy management solution can well meet the demand requirement and significantly reduced the electricity purchase cost. In addition, comparison of results shows that benefits can be acquired from the usage of vehicle to grid and battery energy storage.

This article proposes a charging management of electric vehicles (EVs) in a charging station taking into account different behavioral responses of EV customers. The EV charging problem is decomposed into two subproblems. The first subproblem is called the pricing game and it considers the charging price and the allowable requesting EVs for charging. Included in this subproblem three different EV customer responses to the charging price are developed. The second subproblem is called the power distribution game and it tackles the charging power distribution among the plugged in EVs. Three different EV customer responses to the charging power are also proposed and included here. The proposed solution for each subproblem is reached iteratively in a distributed way. Detailed simulation, experiment, and comparison results are presented to verify the effectiveness and correctness of the proposed charging management with EV customer behaviors.

This article proposes a charging management of electric vehicles (EVs) with a newly presented EV social contribution. The EV charging problem is represented by a generalized Nash equilibrium game where each individual EV tries to minimize its charging cost while satisfying its own charging requirements and respecting the charging facility constraints. The individual EV features a social behavior to potentially contribute in shifting its charging schedule from specific intervals that have insufficient charging power. This shift in the EV schedule will allow more charging power to other EVs that admit stricter charging requirements, i.e., intervals and demands. In this way, the contributed EVs socially help others in reducing their charging costs, which is particularly important during the overload cases in the system. The proposed solution is reached iteratively in a distributed way utilizing the consensus network and found based on the receding horizon optimization framework. Both simulation and experimental results demonstrate the effectiveness and correctness of the proposed social contribution in the charging management for reducing the charging cost of EVs.

Compact, isolated DC-DC converters are required in many applications such as communication terminals. This paper presents a compact, planar Class E2 DC-DC converter via wireless inductive coupling. For high frequency converters working at megahertz (MHz), it is challenging to design the system parameters under the condition of different final loads and voltage ratios. In this paper, a design method is proposed to adjust the voltage ratio of a Class E2 DC-DC converter without changing the turn ratio of the coils. An experimental 6.78 MHz Class E2 converter system with flexible voltage ratio is built, with the coupling coefficient k=0.33 and overall efficiency above 80 %.

This paper studies a photovoltaic (PV) based electric vehicle charging station. It consists of multiple energy components: PV panel, battery and transformer. There exist uncertainties inside the system: stochastic charging behavior of electric vehicles (EV s) and intermittent nature of PV power generation, which present challenges to the design of entire system components. In this paper, the EV charging demand model is firstly developed. Then, the optimal components sizing problem of the charging station is formulated to minimize the entire system economic cost. In the problem formulation, the introduced uncertainties are included and converted into the reliability to guarantee. Then, the optimal size for each component is obtained. Results show that equipping PV panel facilitates the charging station to achieve lower economic cost than that of without PV panel.

The spatial freedom of wireless power transfer (WPT) systems can be improved using a high operating frequency such as several megahertz (MHz). In the conventional compensations the load of the coupling coils is usually assumed to be pure resistive. However, in MHz WPT systems this assumption is not accurate anymore due to the nonneglectable rectifier input reactance. This paper discusses the impedance characteristics of the full-bridge rectifier at MHz and their influence under the series-series, parallel-series, series-parallel, and parallel-parallel compensation topologies. An undesirable nonzero phase (i.e., none unity power factor) is shown to exist at the primary input port, which leads to decreased power transfer capability. In order to minimize this negative effect, the compensation capacitors are optimally designed, and the series-series topology is found to have the smallest phase under load and coupling variations. Finally, an experimental 6.78 MHz system is built up to verify the optimized design of the compensation capacitors. The results show that the average nonzero phase is effectively reduced together with the improved power factor from 0.916 to 0.982.

With the rapid exhaustion of fossil energy, electric vehicles (EVs) become one of the key candidates for the next generation of transportation. Increasingly perfect technology developed makes EVs grow significantly. Therefore, Charging Stations (CSs), as accessories and necessities of EVs, should form a network with optimal planning. Inappropriate CS network design could cause series of negative effects to the popularization of EVs, the layout of the city traffic network and the financial cost of CS network construction, etc. Besides, the charging infrastructure planning for cities with large population and high EV density becomes even difficult. In this paper, an Effective Planning of CSs Network (CSN) is proposed. Comprehensive environmental elements (e.g. cities' and CSs' information, EV charging status, etc.) are considered in CSN. The CSN deals with complicated city planning in giant cities (i.e. large population, high EV density, etc.). Hong Kong is selected as the case study because it can be regarded as a typical giant city. Results show that the proposed CSN can ensure the EVs can find a CS before it is out of power. Besides, the CSN saves ~18% financial cost for the charging infrastructure planning in giant cities.

The charging problem becomes prominent with the increasing number of electric vehicles. It is necessary to built charging station (CS), like the gasoline station, to satisfy the recharging and be convenient for the drivers. In this paper, a new type of charging station integrated with renewable energy source was studied. A hierarchical energy management strategy oriented to real-time application was proposed to handle the uncertainties. To determine the optimal size of the CS by considering multiobjective including economic, environment and battery energy storage system degradation, Monte Carlo simulation was adopted to solve the problem with many uncertainties. We treated battery degradation as a specific objective function. And we obtained the optimal Pareto set. The result demonstrated the optimal decision variable for CS sizing can compromise the objectives as well as realize the reasonable resource dispatch.

A hierarchical distributed energy management for multiple photovoltaic (PV) based electric vehicle (EV) charging stations (PV-CSs) is proposed and analyzed in this paper. In the station level, PV-CSs are modelled as independent players with objectives to stabilize their average available capacity (AAC) of the storage battery tank. Meanwhile, in EV level, EV owners are modeled as players with objectives to maximize their charging power. Then a two level power distribution game is utilized to model the power distribution problem in both station and EV level. Through utilizing a consensus network based learning algorithm, a cooperative and a generalized Stackelberg equilibrium are achieved in station and EV level through a distributed fashion. One case studies, i.e., two station case, is implemented in simulation to verify the performance and effectiveness of the proposed strategy. The simulation results show that the proposed energy management has an excellent performance in both cases and comparing against stations without management.

The papers in this special section focus on cyber-physical systems in green transportation. Ground mobility is being in a paradigm shift toward more efficient and green transportation. Wireless networking, sensing, computing, and control advances have significantly changed the way the society interacts with the physical world. In the context of cyber-physical systems (CPS), transportation systems become highly multidisciplinary. They require an ever-increasing integration of mechanical, electrical/ electronic, control, and information disciplines. Emerging innovative technologies, such as automated driving and electrified vehicles, are also profoundly promoting connection, automation, and electrification of the current transportation sector.

This paper discusses decentralized real-time energy management for multiple-source hybrid energy systems (HESs), which adapts to the sudden change in system configuration, such as due to failure of certain devices. An engine-generator/battery/ultracapacitor (UC) HES is chosen as a case study facilitating the following theoretical discussion. The energy management problem is first modeled as a noncooperative game, in which the different preferences of the energy sources (engine-generator, battery pack, and UC pack) in actual operation are quantified through their individual utility functions. The Nash equilibrium is iteratively reached at each control instant via a learning algorithm. Under the game theory based control, each source or player tends to maximize its own preference. However, its satisfaction level also depends on decisions of others. This real-time interaction in decision making provides the proposed energy management a capability to autonomously adapt to the reconfigured HES. A tuning procedure of weight coefficients in the utility functions also helps to further improve the adaptiveness of the decentralized energy management. Both the simulation and real-time implementation show that the game theory based energy management strategy has a comparable performance to the classical centralized benchmarking strategy. Meanwhile, the decentralized strategy demonstrates an obvious flexibility handling the cases when the configuration of the HES varies both statically and dynamically.

This paper introduces a distributed energy management for islanded DC microgrids with electric vehicles (EVs) penetration. The energy management problem is divided into two stages. The first, named as filtering stage, is controlled through wavelet filter using the ultracapacitor. The second one is modeled as a noncooperative stackelberg game, where the battery energy storage system is designed as a leader and EVs as followers. The preference of the battery energy storage system is designed to extend its cycle life while for each EV's preference is to maximize its charging power. The consensus network is utilised to reach the Nash equilibrium within the followers at each control instant. The simulation results show the power distribution among the system's units throughout one day. Moreover, comparable outcomes with the centralized method have been illustrated under two available power scenarios i.e., two weather profiles.

High frequency wireless power transfer (WPT) such as working at megahertz (MHz) is widely considered to be a promising candidate for charging the lithium-ion batteries of mobile electronic devices. However, in a real battery charging application, the varying battery voltage and charging current will significantly affect the system efficiency and lead to the high power loss in the whole charging process, especially at MHz due to the obvious rectifier input reactance. Moreover, it makes the optimization design of wireless battery charging system more complicated and difficult. In this case, a 6.78-MHz wireless battery charging system is proposed and an optimization design procedure is developed to minimize the average power loss in the whole charging process. By using the circuit model of the wireless battery charging system, the system efficiency is derived and services as the basis for the optimization design. Finally, the experimental results are provided for verification. It shows that the system using the proposed optimization design can achieve a 24.5% reduction of the average power loss compared to the conventional one.

This paper discusses a decentralized energy management for an engine-generator/battery/ultracapacitor (UC) hybrid energy system with fault tolerance analysis. The energy management problem among the energy suppliers and the load is formed into a non-cooperative power distribution game where the engine-generator, the battery pack, the UC pack, and the load are modeled as independent and related players. Each player has an unique objective, i.e., reducing fuel consumption, prolonging battery cycle life, maintaining UC state of charge and satisfying the load demands, represented by different second order polynomial function based utility functions. In this game, a Nash equilibrium is reached at each control instant to give a balanced solution among players. The weight coefficients in the utility functions can be determined through the Pareto optimal solution a multi-objective genetic algorithm. The fault tolerance analysis based simulation shows that the proposed energy management has a flexible and reconfigurable performance under six different case studies.

This paper provides a two-level energy management strategy for a fuel cell-battery-ultracapacitor (UC) hybrid system. In the proposed strategy, the battery and UC packs are seen as an energy storage system (ESS) at the first level and the equivalent consumption minimization strategy is used to distribute load power between this ESS and the fuel cell system. The penalty factor is tuned based on estimated average load power and SOC of the ESS. At the second level, the power distribution between the battery and UC packs is determined using the equivalent series resistance-based control strategy to minimize the energy loss. Then, the performance of the proposed two-level energy management strategy is analyzed in simulation under a realistic load profile. Finally, detailed comparison results show that the two-level energy management strategy can achieve lower hydrogen consumption, compared with the rule-based method.

Simultaneous wireless charging of multiple devices is a unique advantage of wireless power transfer (WPT). Meanwhile, the multiple-receiver configuration makes it more challenging to analyze and optimize the operation of the system. This paper aims at providing a general analysis on the multiple-receiver WPT systems and compensation for the influence of the cross coupling. A two-receiver WPT system is first investigated as an example. It shows that theoretically by having derived optimal load reactances, the important system characteristics can be preserved, such as the original system efficiency, input impedance, and power distribution when there is no cross coupling between receivers. The discussion is then extended to general multiple-receiver WPT systems with more than two receivers. Similar results are obtained that show the possibility of compensating the cross coupling by having the derived optimal load reactances. Finally, the theoretical analysis is validated by model-based calculation and final experiments using real two- and three-receiver systems.

The papers in this special section focus on the toptic of networked energy systems, inclusing their architectures, management, and communications services.

A wireless power transfer system can increase its system frequency to several Megahertz for large spatial freedom. A MHz system usually uses the same compensation as those kHz systems. Traditionally, the rectifier is modeled as a pure resistive load for the coupling coils when designing the compensation capacitors. However, the rectifier input reactance cannot be ignored for MHz systems. This reactance can affect the system resonance and is usually not considered when designing the compensation capacitors. This paper analyzes the rectifier input impedance and discusses its undesirable effects. A non-zero phase is shown to exist seeing into the coupling coils for MHz WPT system. In order to limit the phase, the optimal compensation capacitors are discussed and found. Finally, a 6.78 MHz system is used to verify the proposed optimal compensation method. It shows the phase variation can be limited from the original range [15°-35°] to the optimal range [-5°-5°].

Wireless power transfer (WPT) has shown its potential over conventional charging systems in recent years. However, it is still challenging to determine the power distribution of a multiple-receiver WPT system for its high sensitivity, complex coupling and load relationships. This paper discusses a game theory based control approach for the power distribution of a multiple-receiver WPT system. The power receiver systems (i.e., a receiving coil, a DC-AC rectifier, a DC-DC converter, and an ultracapacitor pack in this paper.) are modelled as independent agents with different preferences under the Matlab simulation environment where the preferences of each agent are represented by utility functions. Then a non-cooperative power distribution game is set up and a generalized Nash equilibrium is found which is used as the reference solution formula to be updated at every control instant. Meanwhile, the generalized Nash equilibrium is found through finding out the variational equilibrium by Karush Kuhn-Tucker conditions (KKT) conditions. The simulation results show that the game theory based control is comparable to the highest efficiency impedance distribution approach in a three-receiver WPT system.

This paper provides an equivalent series resistance-based real-time control method for the battery-ultracapacitor hybrid system. The idea of this control method is that the dynamic load demand is distributed based on the equivalent series resistance ratio of batteries to ultracapacitors, whilst the estimated average load demand based on the past N seconds is supplied by the batteries. In addition, the energy stored in the ultracapacitors is considered for protection purpose. The simulation results verify the effectiveness of the equivalent series resistance-based real-time control method, in terms of the system efficiency, the overall energy loss, and the utilization of the ultracapacitors. Further comparison results show that the efficiency of the proposed real-time control method with well-selected parameter is only 1% lower than that of the dynamic programming method.

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.

In this paper, a state feedback controller is designed via polynomial method for a double inverted pendulum. The polynomial method is first extended into state space. Then based on the equations of motion, the linearized state space model of double inverted pendulum is derived near the upright balance position. The state feedback controller is designed via polynomial method where Ackermann's formula is used to determined the gain matrix. The polynomial-method-based controller design is validated through real experiments. It is shown that the existence of closed-loop zeros in the overall control system imposes limit on the selection of the time constant in polynomial method. In the end, the performance of the controller design is compared with the well-known linear quadratic regulator control. The two controllers share an identical state feedback control configuration, but their design procedures are different. It is found that the two different control methods have a similar performance. However compared with the trial-and-error-based linear quadratic regulator optimal control, polynomial method is much more straightforward in terms of its design procedure due to clear physical meanings of its control parameters.

This paper discusses a game theory based control of an engine/generator-battery-ultracapacitor hybrid energy system. The engine/generator, the battery and ultracapacitor packs are modelled as three independent agents to show their different preferences under the Netlogo environment. The preferences of these three energy components are represented by utility functions. Then a non-cooperative current control game is set up and a Nash equilibrium is found which is used as reference solution formula to be updated at each control instant. The weights in the utility functions are chosen based on the location of the knee point in the Pareto set. The simulation results show that the game theory based control has a comparable performance with the average load demand-based control without knowing the pre-knowledge of the test trip.

This paper provides a quantitative and comparative study on efficiencies of a battery semi-active hybrid energy storage system (HESS) and a battery-only system. The discussion is based on the equivalent series resistance (ESR) circuit models and a pulsed current load. It is theoretically proved that the efficiency difference between the two systems depends on the variance of the load current, the average load current, and the internal resistance of the battery pack. A threshold variance is then accurately derived, above which the battery semi-active HESS becomes more energy efficient. This threshold decreases with an increasing internal resistance of the battery pack and/or a decreasing average load current. Therefore, the best usage of ultracapacitors is to combine with batteries designed for low cost (i.e. a large internal resistance), and supply the dynamic part of a current load with a high peak-to-average ratio. Finally, JC08 driving cycle-based simulation validates the theoretical analysis.

The seven papers in this special section explore the deployment of electrification in transportation systems.

Wireless power transfer (WPT) has attracted an ever increasing interest from both industry and academics over the past few years. Its applications vary from small power devices such as mobile phones and tablets to high power electric vehicles and from small transfer distance of centimeters to large distance of tens of centimeters. In order to achieve a high-efficiency WPT system, each circuit should function at a high efficiency along with the proper impedance matching techniques to minimize the power reflection due to the impedance mismatch. This paper proposes an analysis on the system efficiency to determine the optimal impedance requirement for coils, rectifier, and dc–dc converter. A novel cascaded boost–buck dc–dc converter is designed to provide the optimal impedance matching in WPT system for various loads including resistive load, ultracapacitors, and batteries. The proposed 13.56-MHz WPT system can achieve a total system efficiency over 70% in experiment.

In this paper, a polynomial-based design of inertia ratio controllers is discussed for the vibration suppression in two-mass system. A tradeoff relationship is shown to exist between damping and robustness performances in the control problem. A desirable inertia ratio of 5/16 is derived at which IP control provides a proper damping. Then two approaches for the control of equivalent inertia ratio are discussed without/with load velocity feedback. “Resonance ratio control” is capable of providing a sufficient damping for large inertia ratios by using only drive velocity feedback. However, a negative derivative gain is necessary, which leads to a poor robustness. By using both drive and load velocity feedback, the equivalent inertia ratio can be exactly specified as 5/16. The proposed “inertia ratio controller” design shows an obvious improvement in terms of both damping and robustness performances. All the experimental results validate the polynomial-based theoretical analysis and controller design. The demonstrated generality and the explicit expression of damping indicate the promising prospect of the polynomial-based controller design for solving more complicated control problems.

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.