Improved utilization for “smart parking systems” based on paging technique

Considering the rapid urbanization and the road congestion, the development of smart parking solutions becomes more crucial, especially in terms of economic interests. Thanks to IoT-connectivity and the cloud-integrated platforms, drivers can easily find a vacant parking lot with smart parking services. This paper intervenes in the profit of parking management systems. The paper proposes a new technique “paging technique” which increases the utilization factor of parking slots. The proposed method takes advantage of the idle time that exists between two successful parking services in the same slot. Besides, it investigates the possibility of using the idle times from different parking slots to provide a continuous parking time for an additional car. The paging technique is optimally implemented using mixed-integer linear programming that maximizes the utilization factor for the parking slots with minimum car transitions. Moreover, a data model for the parking management system has been constructed while considering the three major customers, namely, regular, prepaid, and walk-in customers. The difference between fixed and dynamic pricing for parking has been investigated. The technique has been validated using GAMS optimization software and hardware using DSP with Coin-or branch and cut solver (CBC) under real-life conditions. The statistical results prove that the revenue for the proposed parking system has increased significantly. Finally, a comparative analysis is performed, benchmarking our proposed method against recent competing algorithms in real world applications to demonstrate its superiority

Power management optimization of electric vehicles for grid frequency regulation : comparative study

Electric vehicles (EVs) have shown promise in providing ancillary services, e.g., frequency regulation. This is mainly due to their capacities and fast response. On the contrary, the rapid integration of EVs in the grid poses challenges, such as frequency and voltage stability. In order to mitigate the above-mentioned issues, several dispatching strategies have been introduced in the recent literature to optimize the charging/discharging rates of EVs. In this paper, a comparative study of power management strategies for secondary frequency regulation (SFR) employing a fleet of EVs is presented. A hierarchical control scheme is employed to compare two cases, namely control at the charging station (CS) level and novel control at the EVs level. Under both cases, a multi-objective optimization approach is utilized to define the optimal charging and discharging rates of EVs using a pattern search algorithm. Furthermore, the performance of the two models is experimented under contingency cases, a notable contribution of this study. Finally, simulations are carried out using OPAL-RT real time simulator to validate the performance of the two models based on real-time traces obtained from Pennsylvania, New Jersey, and Maryland (PJM) interconnection and California independent system operator (CAISO). To further validate the proposed model, a comparison with a mixed-integer linear programming (MILP) based model is presented

Data-driven-based vector space decomposition modeling of multiphase induction machines

For contemporary variable-speed electric drives, the accuracy of the machine's mathematical model is critical for optimal control performance. Basically, phase variables of multiphase machines are preferably decomposed into multiple orthogonal subspaces based on vector space decomposition (VSD). In the available literature, identifying the correlation between states governed by the dynamic equations and the parameter estimate of different subspaces of multiphase IM remains scarce, especially under unbalanced conditions, where the effect of secondary subspaces sounds influential. Most available literature has relied on simple RL circuit representation to model these secondary subspaces. To this end, this paper presents an effective data-driven-based space harmonic model for n-phase IMs using sparsity-promoting techniques and machine learning with nonlinear dynamical systems to discover the IM governing equations. Moreover, the proposed approach is computationally efficient, and it precisely identifies both the electrical and mechanical dynamics of all subspaces of an IM using a single transient startup run. Additionally, the derived model can be reformulated into the standard canonical form of the induction machine model to easily extract the parameters of all subspaces based on online measurements. Eventually, the proposed modeling approach is experimentally validated using a 1.5 Hp asymmetrical six-phase induction machine

Investigation of six-phase surface permanent magnet machine with typical slot/pole combinations for integrated onboard chargers through methodical design optimization

This article presents an analytical magnetic equivalent circuit (MEC) modeling approach for a six-phase surface-mounted permanent magnet (SPM) machine equipped with fractional slot concentrated winding (FSCW) for integrated onboard chargers. For the sake of comparison, the selected asymmetrical six-phase slot/pole combinations with the same design specifications and constraints are first designed based on the parametric MEC model and then optimized using a multiobjective genetic algorithm (MOGA). The commercial BMW i3 design specifications are adopted in this article. The main focus of this study is to achieve optimal design of the SPM machine considering both the propulsion and charging performances. Thus, a comparative study of the optimization cost functions, including the peak-to-peak torque ripple and core losses under both motoring and charging modes and electromagnetic forces (EMFs) under charging, is conducted. In addition, the demagnetization capability in the charging mode and the overall cost of the employed machines are optimized. Since the average propulsion torque is crucial in electric vehicle (EV) applications, it is maintained through the design optimization process. Furthermore, finite element (FE) simulations have been carried out to verify the results obtained from the analytical MEC model. Eventually, the effectiveness of the proposed design optimization process is corroborated by experimental tests on a 2-kW prototype system

General Current Control of Six-Phase-Based Non-Isolated Integrated On-Board Charger with Low Order Harmonic Compensation

Electric vehicle charging technology has recently witnessed massive developments due to its significant role in the ever-growing number of electric vehicles on the market. The integrated on-board charger technology (IOBC) represents an effective and attractive solution to reduce EV size, cost, and weight. IOBC technology employs propulsion components, such as the motor and its converter, in the charging process. The main objective of IOBC is to achieve the maximum charging current with zero average/pulsating torque so that mechanical interlocking can be dispensed. Recently, some of the IOBC topologies have adopted machines with six-phase stators to exploit the many advantages of multiphase-based systems. This paper investigates the effect of the winding design, namely, chorded or un-chorded designs, as well as the winding configuration, namely, dual three-phase, asymmetrical, or symmetrical winding configurations, on the current quality of a six-phase-based non-isolated IOBC. The relation between the winding design and the induced low order harmonics in the charging current is first clarified. The required current controller structure is then proposed, which ensures balanced grid line currents with high quality, under either healthy or one-phase fault conditions. Finally, a comparative study between all available designs with the proposed current controller is carried out to validate the theoretical findings

General Current Control of Six-Phase-Based Non-Isolated Integrated On-Board Charger with Low Order Harmonic Compensation

Electric vehicle charging technology has recently witnessed massive developments due to its significant role in the ever-growing number of electric vehicles on the market. The integrated on-board charger technology (IOBC) represents an effective and attractive solution to reduce EV size, cost, and weight. IOBC technology employs propulsion components, such as the motor and its converter, in the charging process. The main objective of IOBC is to achieve the maximum charging current with zero average/pulsating torque so that mechanical interlocking can be dispensed. Recently, some of the IOBC topologies have adopted machines with six-phase stators to exploit the many advantages of multiphase-based systems. This paper investigates the effect of the winding design, namely, chorded or un-chorded designs, as well as the winding configuration, namely, dual three-phase, asymmetrical, or symmetrical winding configurations, on the current quality of a six-phase-based non-isolated IOBC. The relation between the winding design and the induced low order harmonics in the charging current is first clarified. The required current controller structure is then proposed, which ensures balanced grid line currents with high quality, under either healthy or one-phase fault conditions. Finally, a comparative study between all available designs with the proposed current controller is carried out to validate the theoretical findings