Disha Harwalkar

As an MSc graduate in Electrical and Electronics Engineering from the University of Greenwich I have developed a broad skill set that includes expertise in design, analysis, testing, and optimization of engineering systems. A reliable, organized, hardworking and confident individual who is skilled in effective communication. My hardworking and resourceful approach enables me to deliver results even in demanding situations. My experience in project support and problem-solving at the university has equipped me with the necessary skills to handle complex engineering challenges. Additionally, I have demonstrated leadership qualities as a team leader for multi-ethnic group projects during my studies at University of Greenwich.

• Dissertation: Individual Research Project,(University of Greenwich)- This research examined the impact of temperature on batteries for electric vehicles and compared the effectiveness of using a cooling system. Cold plates with a mixture of ethyl-glycol and water were used to lower the battery temperature and compared to using only water. A MATLAB/Simulink model was developed, Proteus schematic was built and a mini prototype was built to demonstrate experimental analysis to compare the performance of the battery with and without the cooling system.
• Dissertation: Analytical Study Of Correlation Between Demand And Renewable Energy Forecasting Using Data Mining/Analytics,(Acharya Institute of Technology)- To meet the increasing demand for electricity due to population growth and urbanization, effective load forecasting method was conducted using load, solar, and wind data from Germany for time series forecasting. Linear Regression and LSTM-based RNN methods were used to forecast renewable energy sources, solar and wind, and conventional load. Correlation coefficient algorithms, Pearson's and Spearman's, were used to find the correlation between the load data and solar and wind data. The platform used for coding in Python was Spyder. Mathematical calculations were performed to cross-verify theoretical and practical values. The study revealed how much energy generated from solar and wind can meet the day-to-day load requirement.
• Mini project on RFID technology based attendance system Using 8051 microcontroller,(Acharya Institute of Technology) -Built an automated mechanism using 'C' program for the university which never existed to track student attendance. This made the attendance systems more systematic.
• Mini Project: Control Of Speed And Direction Of A Stepper Motor Using Ultrasonic Sensor And Hall Effect Sensor,(University of Greenwich)- To control the speed and direction of a simple permanent magnet stepper motor, two sensors namely the ultrasonic and the hall effect sensors were used. The hall effect sensor changes the direction of the motor with a magnetic field, while the ultrasonic sensor alters the speed by measuring distance. The project used two LEDs to indicate motor direction, and an Arduino as the motor controller programmed in C++.
• Mini project: IOT DC motor predictive maintenance system,(University of Greenwich)- A mini prototype to demonstrate how a predictive maintenance on a DC motor is done, a D1 LOLIN MINI PRO Wi-Fi enabled microcontroller and the INTERNET OF THINGS (IOT) was used. To achieve this, intelligent devices such as sensors were integrated and embedded onto the DC motor to enable optimum forward and reverse motor control, motor speed measurements, motor temperature measurement, and ambient temperature and humidity measurement. The BLYNK application was used as the IOT platform to provide a simple interface control and web-based data logging system.
• Mini Project: Design And Simulation Of Chebyshev - Bandpass Filter With Folded Stepped-Impedance Resonator Using AutoCAD Software,(University of Greenwich)- This project aimed at designing and the simulation of a 4th order Chebyshev bandpass filter which is usually used for ultra-high frequency applications. The filter designed was with a passband ripple of 0.0431 and a return loss of -20dB with a center frequency of 800MHz, fractional bandwidth of 6% and a characteristic impedance of 50Ω.
• Project On Image Processing,(University of Greenwich)-Three filtering techniques: conservative filtering, mean filtering, and the median filtering on a given test image of a cat was done. A comparative analysis between the three filters was done. In addition to this, in order to further enhance the image processing which can be proven beneficial to the user, image sharpening using Laplace filtering was performed to highlight the details of the image. Along with this, edge detection using Sobel operation to detect the edges was done. For the easier analysis of all the image processing techniques these were interfaced with a GUI application.