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Solar energy can function as a supplementary power supply for other renewable energy sources. On average, Vellore region experiences approximately six hours of daily sunshine throughout the year. Solar photovoltaic (PV) modules are necessary to monitor and fulfill the energy requirements of a given day. An artificial neural network (ANN) based maximum power point tracking (MPPT) controller is utilised to regulate the solar photovoltaic (PV) array and enhance its output. The utilisation of this controller can enhance the efficiency of the module even in severe circumstances, where reduced current and torque ripples will be observed on the opposite end. The motorised vehicle has the capability to function at its highest torque level in different load scenarios as a result. The proposed method is expected to provide advantages in various electric vehicle (EV) applications that require consistent velocity and optimal torque to satisfy the load conditions. The study employs a solar battery that is linked to an SVPWM inverter and subsequently a DC-DC boost converter to supply power to the load. An Artificial Neural Network (ANN) based Maximum Power Point Tracking (MPPT) control system is proposed for a solar battery powered Electric Vehicle (EV) and the system’s performance is evaluated by collecting and analysing data under adjustable load conditions to obtain constant parameters such as speed and torque. The MATLAB® Simulink® model was utilised for this purpose.

This paper aims to fabricate pineapple leaf fibre epoxy reinforced with three different orientations which are unidirectional, bidirectional and inclined 45°. E-glass fibre is also introduced in every orientation to observe the change in strength. Fabrication of all these epoxies reinforced pine apple fibre is being done by Hand Layup technique. Two tests are done on these composites that are Tensile Test and Flexural Test. The tensile strength of unidirectional oriented fibre is increased when the E-glass is introduced with composites. The tensile property of unidirectional fibre is reinforced when the E-glass is brought together with composites. The maximum tensile strength was observed in the E-glass unidirectional pineapple fibre composite. Optimum Flexural strength is observed for inclined 45° specimen without E-glass reinforcement, whereas with the introduction of E-glass unidirectional composite maximum flexural strength is yielded. From the results, it can be proposed that Pineapple Leaf Fibre (PALF) reinforced with epoxy and E-glass showed best characteristics for unidirectional orientation of fibre for tensile and in flexural loading. Based on the results obtained, this pineapple composite material is recommended to use for lightweight packaging applications like food industries. [ABSTRACT FROM AUTHOR]

This research highlights the vibration analysis on worm gears at various conditions of oil using the experimental set up. An experimental rig was developed to facilitate the collection of the vibration signals which consisted of a worm gear box coupled to an AC motor. The four faults were induced in the gear box and the vibration data were collected under full, half and quarter oil conditions. An accelerometer was used to collect the signals and for further analysis of the vibration signals, MATLAB software was used to process the data. Symlet wavelet transform was applied to the raw FFT to compare the features of the data. ANN was implemented to classify various faults and the accuracy is 93.3%. [ABSTRACT FROM AUTHOR]