The optimisation of energy generation in a photovoltaic (PV) system is necessary to let the PV cells operate at the maximum power point (MPP) corresponding to the maximum efficiency. Since the MPP varies, based on the irradiation and cell temperature, appropriate algorithms must be utilised to track the MPP. This is known as maximum power point tracking (MPPT). Different MPPT algorithms, each with its own specific performance, have been proposed in the literature. A so-called perturb and observe (P&O) method is considered here. This method is widely diffused because of its low-cost and ease of implementation. When atmospheric conditions are constant or change slowly, the P&O method oscillates close to MPP. However, when these change rapidly, this method fails to track MPP and gives rise to a waste of part of the available energy. An adaptive P&O method is proposed in this study that has faster dynamics and improved stability compared to the traditional P&O. The MPPT algorithm was set up and validated by means of numerical simulations and experimental tests, confirming the effectiveness of the method
Abstract:The power extracted from PV arrays is usually maximized using maximum power point tracking algorithms. One of the most widely used techniques is the perturb & observe algorithm, which periodically perturbs the operating point of the PV array, sometime with an adaptive perturbation step, and compares the PV power before and after the perturbation. This paper analyses the most suitable perturbation step to optimize maximum power point tracking performance and suggests a design criterion to select the parameters of the controller. Using this proposed adaptive step, the MPPT perturb & observe algorithm achieves an excellent dynamic response by adapting the perturbation step to the actual operating conditions of the PV array. The proposed algorithm has been validated and tested in a laboratory using a dual input inductor push-pull converter. This particular converter topology is an efficient interface to boost the low voltage of PV arrays and effectively control the power flow when input or output voltages are variable. The experimental results have proved the superiority of the proposed algorithm in comparison of traditional perturb & observe and incremental conductance techniques.
This study deals with direct torque control (DTC) of induction motor drives when a multilevel inverter is involved. The proposed control technique is finalised to reduce the amplitude of torque oscillations and to improve the motor dynamic response regardless of operating speed conditions while assuring a satisfactory input current distortion. This is achieved by using a special look-up-table built with a novel approach. The control itself is based on the application in each sampling interval of one or two voltage vectors suitably selected, in order to ensure low electromagnetic torque ripple in steady-state operations and fast dynamic behaviour in transient operations. In the algorithm, the converter voltage vectors selection is carried out by using a novel look-up table whose entry points are computed by means of a specialised relation, starting from the outputs of multilevel hysteresis controllers. The suggested method, suitable for a generic multilevel inverter, is detailed for a neutral point clamped three-level inverter. The proposed algorithm is validated by several numeric a lr e s u l t s ,a n dc o m p a r e dw i t haD T Ca l gorithm based on a traditional threespeed range look-up tables. Finally, some experimental results, obtained with a scale laboratory setup, are shown, discussed and compared with the numerical ones.
Electric propulsion represents the new research frontier in the future ship technology. There are different hybrid topologies requiring sizing criteria of components and related control strategies, finalized to maximize different objective functions: weight and space reduction on-board, fuel economy, pollution reduction or optimized efficiencies. In the paper sizing criteria of on-board sources and energy storage systems are proposed for a hybrid series architecture for a typical "passenger boat". Two different design criteria are proposed for a series architecture: a criterion aims to ensure that the engine-generator group runs at fixed speed and power, whereas the other consists to run the engine at variable power and speed. The procedure for an optimal design of an on-board sources is set up and validated by numerical applications on a 23 m long passenger boat having a displacement of 37 tons.
Despite the yearly rise in the market quota of full electric vehicles, the main limitations on the deployment of electric vehicles are the real performances of the battery storage during operation. In this study, the authors focus on hybrid electrical storage systems composed of lead acid batteries and supercapacitors. Two different coupling methods are investigated: (i) the direct parallel coupling of the two storage devices and (ii) coupling by means of a step-up converter between the supercapacitor bank and direct current (DC) link of the entire power-train, where lead acid batteries are also connected. A specific control strategy is proposed and implemented in the step-up converter to guarantee the correct power management of the power train and in particular: (i) to save the power request to the lead acid battery pack, (ii) maintain an adequate state of charge of the supercapacitor bank, and (iii) guarantee an adequate voltage level on the DC link. A prototype of the hybrid battery, integrating the proposed control technique, was realised and tested on a real forklift. The performances of the entire power-train were experimentally measured in a warehouse test cycle emulating a typical daily working cycle.
In this study, the design optimisation of a synchronous reluctance machine for light electric vehicles is proposed, to increase efficiency and reduce torque ripples. The existing machine was structurally optimised, using dedicated genetic algorithms, replacing only the rotor and keeping the stator and it's winding untouched. Starting from the original design of the rotor implemented in Flux2D, a finite element analysis software, and the genetic algorithm optimisation implemented in Matlab, a complex co-simulation was accomplished to obtain a rotor architecture that increases the machine's performances and decreases the torque ripples. By this, performing rotor skewing is not needed any more, hence the torque loss due to it was cancelled. The optimised rotor design increases the machine performances by higher mean torque, no skewing, <8% torque ripples, higher efficiency and better inductance characteristics. Comparative results obtained both in simulations and experimental measurements prove positive outcomes of the optimisation process.
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