A vehicular energy network (VEN) enables energy transfer by leveraging electric vehicles as mobile carriers through wireless exchange across large geographic areas. This article presents a scalable and robust framework for energy routing in stochastic VENs with the objective of minimizing transmission loss. The problem is formulated as a graph generalized flow optimization, solvable to global optimality via linear programming. To ensure scalability, a flow-guided graph reduction method is proposed, which preserves critical supply-demand connectivity by prioritizing high-impact routes based on vehicular flow patterns. Building upon this, a route-guided time-expanded graph construction strategy is developed to avoid exhaustive temporal replication by generating only time-relevant nodes and arcs along active routes. To address long-horizon stochasticity, a long short-term memory-based model predictive control framework is designed, which captures both randomness and uncertainty via data-driven forecasting and residual-aware robust correction under a rolling-horizon decomposition. The proposed methods are validated on 100 real-world U.S. datasets, demonstrating significant gains in computational efficiency, scalability, and solution robustness across both time-invariant and time-varying VENs.

This paper introduces a novel multi-frequency cascade disturbance observer (MF-CDOB) designed for permanent magnet synchronous motor (PMSM) drives. Unlike conventional disturbance observer (DOB) techniques, the proposed MF-CDOB employs a cascaded arrangement of multiple DOBs. This unique structure effectively decouples the frequency responses, enabling independent tuning for the rejection of both aperiodic and harmonic disturbances. Developed in the discrete-time domain, the method offers enhanced real-time disturbance rejection without compromising transient performance. Preliminary experimental results validate that the MF-CDOB significantly reduces harmonic content and improves current regulation compared to traditional control schemes.

Variations in coupling coefficient and load impedance pose significant challenges to achieving a stable constant voltage (CV) output in wireless power transfer (WPT) systems, particularly for multi-frequency multi-pickup applications. This article presents an improved LCC topology designed for multi-frequency multi-channel WPT to ensure CV characteristics under such conditions. The proposed network facilitates simultaneous power transfer on multiple frequency channels with key contributions including: 1) enabling load-independent constant current (CC) output per channel at the primary side; 2) realizing coupling coefficient-independent CV output per channel at the pickup side by adopting a closed-loop control strategy. Both merits ensure stable power delivery regardless of positional misalignment or load fluctuations. Theoretical analysis addresses the design principles and parameter selection criteria. Verification results validate the effectiveness of the proposed topology in maintaining CV output across multiple channels under varying coupling and load conditions, demonstrating its suitability and effectiveness.

The dynamic wireless charging (DWC) system based on wireless charging lanes (WCLs) is an important component of smart cities, allowing electric vehicles (EVs) to charge while moving. It is necessary to establish a user-oriented real-time DWC navigation system to achieve the joint optimization of EV routing and charging. However, the modeling characteristics of DWC and the risk preferences of EV owners towards congested WCLs are completely different from those in traditional wired charging. Furthermore, optimal EV charging navigation is always challenging without prior knowledge of uncertainty in electricity prices and traffic conditions. This paper first proposes a novel dynamic charging routing model for individual EVs to minimize travel and charging costs, and reformulates it as a twostep optimization problem to facilitate feature extraction. Then, mirror-symmetrical Dijkstras algorithm (MSDA) is proposed to solve the reformulated model in linear time and extract advanced features from the stochastic information. By feeding the system state containing extracted features into the deep Q network (DQN) in an event-triggered manner, the near-optimal charging navigation strategy is finally obtained. The proposed MSDADQN approach not only efficiently extracts low-dimensional interpretable input features, but also adaptively learns the unknown dynamics of system uncertainty. Numerical results based on simulated and real-world data validate the proposed approach.

Electric vehicle energy network (EVEN) enables the transmission of renewable energy from rural to urban area by the flexibility of EVs via energy exchange. In this paper, (dis)charging behavior modelling and bidirectional charging station (BCS) deployment optimization are addressed, since they are crucial in EVEN for EV accommodation, renewable energy utilization, drivers’ profitability estimation, operators’ cost assessment, and financial policy establishment. A novel stochastic Markov (dis)charging behavior model is proposed to calculate the spatiotemporal load pattern considering the realistic factors such as personal features, state of charge (SoC), electricity price, and BCS locations. Unlike most works ignoring energy trading, six scenarios are explored: (S1) no trade; (S2) trade in main battery. (S3) trade in extra battery. (S4) trade in extra ultracapacitor; (S5) trade in both main and extra battery; (S6) trade in both main battery and ultracapacitor. Also, a multi-objective BCS deployment strategy is newly designed, aiming at minimizing installation cost and driver’s electricity bill, while quality of service (QoS) and voltage stability are ensured. An improved hybrid algorithm is developed, which combines hill climbing for enhanced exploitation and particle swarm optimization for better evolvement based on genetic algorithm framework. The simulation validates the fitting ability of charging model, the effectiveness of parameter selection algorithm and the deployment approach. Comparing 6 scenarios, benefits of energy trading in EVEN is confirmed and the superiority of ultracapacitor for trading is demonstrated. The feasibility of financial policies is also studied, and certain guidance is provided for drivers to improve their cost.

The high-temperature superconducting permanent magnet synchronous machine (HTS-PMSM) has attracted great attention from industries and researchers because of its higher torque density, higher power density, and higher system efficiency. Considering the stator current of HTS-PMSM is supposed to be as clean as possible, the multiple-level inverter is more suitable for the HTS-PMSM. In addition, similar to the conventional PMSMs, the unknown load disturbance can obviously lead to a speed drop. To solve the issues above, this paper proposed a fast finite-time speed control of a three-level T-type inverter for the HTS-PMSM, combined with model predictive control of the current loop. The proposed control method can ensure that the HTS-PMSM can have the ability to resist load disturbances or changes. Finally, the simulation results verify the effectiveness of the proposed control method.

Traffic energy routers (TERs) are wireless power infrastructures that support the trading of electric vehicles (EVs) in the energy market without physical cables. This paper proposes a TER deployment model for wireless energy trading. The objective is to decide which road junction should be electrified into a TER and how long it is. In this paper, the ultracapacitor is utilized due to the advantages of long-life cycles, high power handling capacity and charging/discharging efficiency. Firstly, the number of EVs stopped at each road junction due to red traffic lights is estimated. Secondly, referring to the current electricity price, the charging and discharging demands are predicted. Thirdly, the predicted demand is revised according to whether the EVs are on the electrified paths and the charging state of ultracapacitors. Hence, the trading profiles in the spatial and temporal domains are obtained. Finally, a multi-objective deployment optimization model is designed, aiming to minimize the installation cost and maximize the drivers' profits. Simulations are carried out to study the energy trading behaviors and the optimal deployment strategy. Compared with the full deployment case, the optimal deployment in our paper uses 2.3% cost while earning 38.0% profit.

This paper proposes and implements a stepless frequency regulation method for wireless power transfer (WPT) with a simple LC compensation network to provide load-independent transmitter current. It should be mentioned that the capacitor in LC compensation network is controlled by a switch. Different from previous switched capacitor compensation networks, which can only select a limited number of resonant frequency points, this model can choose the resonant frequency arbitrarily in a wide frequency range. In theory, the frequency range can be controlled from a few kilohertz to hundreds of kilohertz. The key is controlling the turn-on time of the switch and adjusting the activation time length of the controlled capacitor in every WPT cycle. Therefore, the proposed system is very suitable for multi-frequency WPT, as the system can work at full resonance with practically arbitrary frequency. A Simulink simulation serves for verification, and the results prove the system can change the resonant frequency from 100 kHz to 300 kHz continuously while keeping the transmitter current load-independent.

A vehicular energy network (VEN) uses electric vehicles (EVs) to transport energy across a wide geographical area. EVs can charge and discharge wirelessly at road junctions while moving and, thus, transfer energy between junctions. In this article, we propose a method to optimally route energy from multiple energy-supplying junctions to multiple energy-demanding junctions while minimizing energy loss in four different VEN scenarios: 1) a time-invariant VEN; 2) a VEN with time-varying vehicular flows and energy demands; 3) a VEN with time-varying vehicular flows and time-averaged demands; and 4) a VEN with significant storage capacities at junctions. The method employed to solve these scenarios is to model the VEN as a graph specific to each scenario, and then solve the generalized flow problem on the graph. Simulations are performed on all four scenarios and show that transmission efficiency improves when a small number of long vehicular routes are introduced, and when storage capacities at junctions increase. The error in approximating a time-varying VEN as a static VEN is also investigated.

Transportation electrification has attracted much attention in modern society. Among all electrified transportation tools, electric vehicle (EV) is absolutely the one that has great potential to compete with and further take the place of traditional fossil fuel vehicles. This article is to outline and investigate advanced electric machines and their control strategies for EV applications. The key is not only to reveal new design ideas, topologies, structures, methodologies, control strategies, pros and cons, and foresight for advanced electric machines but also to fully integrate these ideas into practical EV applications. This critical review will clarify the development trends of electric machines and their controls.

In this paper, a wireless bipolar drive has been proposed and implemented for AC application, which not only performs selective wireless power transfer (WPT), but also secondary-converterless operation for frequency-controllable AC output. The key is to use the proposed self-drive circuit based on the selective WPT with two different resonant frequencies. Besides, the inductor-capacitor-inductor (LCL) compensation network is newly adopted to achieve power equalization so that only one transmitter is needed to serve two receivers and control the low-frequency AC output. As a result, there is no additional battery, controller, and converter at the secondary side and hence the system robustness can be significantly improved. Finally, experimental results are offered to verify the proposed topology.

In this paper, a novel kind of wireless motors, namely, the LCC-compensated wireless switched reluctance motor, is proposed and implemented. The definite advantages are that there is no power converter at the motor side and particularly no switched-capacitor array at the transmitter side to realize the multiple-frequency operation. The key is to develop an LCC compensation involving an inductor and two capacitors (the so-called LCC) for a multiple-frequency wireless power transfer system. As a result, only one transmitter is needed to targetedly feed three receivers, which directly energize the three phase windings of the motor. Particularly, there is no need to control switched capacitors to change the resonant frequency of the transmitter. Meanwhile, the burst firing control method is employed to realize the speed control. Both calculation and experimental results are presented to validate the feasibility of the proposed system. In the system prototype, the transmission distance can reach up to 150 mm and the transmission efficiency can be achieved up to 80%.

This paper presents a quantitative comparison of three topologies of double-sided long-stator type permanent magnet linear machines (PMLMs) as possible candidates for the ropeless elevator propulsion system. First, the parameters of each PMLM topology are designed using the same criteria. Then the finite element method (FEM) is employed to evaluate the performance of each topology. Specifically, the translator mass, propulsion forces, detent forces, and no-load EMFs are analyzed and compared. The quantitative comparison results show that the Halbach array PMLM configuration is preferable for the ropeless elevator application because of its small detent force as well as low total mass.

The proposed fault-tolerant flux-reversal doubly-salient (FT-FRDS) magnetless motor drive consists of armature winding for driving and DC-field winding for field excitation. The purpose of this paper is to investigate two remedial strategies for fault-tolerant operations of the proposed motor drive under short-circuit faults. First, short-circuit phase can be disabled and the short-circuit fault can then be regarded as the open-circuit fault. By reconstructing the healthy armature phases, the reduced torque can be remedied and this is known as the fault-tolerant brushless AC (FT-BLAC) operations. Second, short-circuit fault can also be remedied based on the DC-field regulation alone, and this is known as the fault-tolerant DC-field (FT-DC) operation. These two remedial operations are compared and verified by the finite-element-method (FEM).

This paper deals with control of a linear magnetic-geared permanent-magnet machine for Archimedes wave swing based wave power generation using maximum power point tracking (MPPT). Firstly, the linear magnetic-geared permanent-magnet generator structure is presented. The machine modeling is established based on finite element analysis (FEA). Secondly, by analyzing the dynamic model of wave power, the MPPT algorithm for direct-drive wave power generation is developed. Then, the performance for maximizing wave power absorption is verified and evaluated by the circuit simulator. The results verify that the MPPT algorithm is valid for the direct-drive wave power generation.

In this paper, a new hybrid-excited flux-switching (HEFS) machine is proposed with the outer-rotor configuration, which possesses the distinct feature of fault-tolerant operation. Comparing with the conventional permanent-magnet (PM) machine, it combines merits of flux control, high mechanical integrity, and low-cost. Furthermore, its fault-tolerant feature ensures its continuous operation in the event of winding faults. Hence, a new 12/10-pole HEFS machine is designed and implemented in this paper. By using time-stepping finite element method, open circuit (OC) fault and short circuit (SC) faults on the armature winding are investigated in the proposed machine for the fault-tolerant operation. The phase-current reconfiguration and flux control are applied for the remediation of the OC fault, while the SC faults is remedied by the phase-current reconfiguration merely. Both approaches demonstrate their good performances for the fault-tolerant operation.

Electric vehicles (EVs) are regarded as one of the most effective tools to reduce the oil demands and gas emissions. And they are welcome in the near future for general road transportation. When EVs are connected to the power grid for charging and/or discharging, they become gridable EVs (GEVs). These GEVs will bring a great impact to our society and thus human life. This paper investigates and discusses the opportunities and challenges of GEVs connecting with the grid, namely, the vehicle-to-home (V2H), vehicle-to-vehicle (V2V), and vehicle-to-grid (V2G) technologies. The key is to provide the methodologies, approaches, and foresights for the emerging technologies of V2H, V2V, and V2G.

This paper presents a permanent magnet linear vernier (PMLV) machine which is dedicated for low-speed direct-drive applications. Firstly, the machine operation principle is discussed, and the preliminary design approach is formulated. Then, by applying the analytical calculation method for solving the magnetostatic field problem, the machine structure, especially the stator toothed-pole structure which acts on the field modulation function is optimized. Finally, a PMLV machine is prototyped and implemented for direct-drive wave power generation. Both analytical calculation and experimental verification are given to verify its performances.

With ever-increasing oil prices, there is fast growing interest in hybrid electric vehicles (HEVs) globally. Thus, it is a pressing need for researchers to develop emerging energy-efficient devices for various kinds of HEVs, including the micro hybrids, mild hybrids, and full hybrids. In this paper, three key emerging energy-efficient technologies are identified and discussed: 1) the thermoelectric waste-heat recovery and temperature control systems for all hybrids, especially micro hybrids; 2) the integrated-starter-generator for mild hybrids; and 3) the electronic continuously variable transmission propulsion for full hybrids