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Kunal Thakkar

Kunal Thakkar

Graduate Automotive Engineer with MSc from UK
Pune, Pune

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About Kunal Thakkar:

An Automotive engineer graduate with experience in ARB mount topology optimization on Hypermesh Optistruct for McLaren Automotive, UK. Static and Dynamic pressure CFD simulation on ANSYS for Atlas Copco Gecia, India. Experienced in CAD Modelling for the college FSAE team in the Chassis Department. Possesses the willingness to learn and work cooperatively within team environments. Computer competencies include various simulation programs such as AVL Boost, Solidworks and Autodesk. Eager to work on the new adoptions of the upcoming changes taking place in the automotive industry.

Experience

  • Received a First Class with Distinction in Bachelor of Technology in Mechanical Engineering (VIIT Pune, India, 2021) & First Class in Master of Science in Automotive Technology (Cranfield University, UK 2023).
  • Led as a team leader a group work project for McLaren Automotive for designing ARB Mounts (Anti-roll Bar) volume optimisation using Hypermesh (Optistruct). (Cranfield, UK 2022)
  • Analysed data to determine the best flywheel for cooling, resulting in increased efficiency by 10% for Atlas Copco Gecia, Pune, Maharashtra. (2020-21)
  • Led Chassis Team Division for Formula Student Competitions for a year. (Pune, Maharashtra 2018-19)

Education

MSc in Automotive Engineering, Cranfield University, Cranfield, UK


Modules: Vehicle Electrification and Hybridisation, Powertrain Simulation and Performance, Vehicle Design Propulsion and Performance, Automotive Control and Simulation, Vehicle Dynamics, Vehicle Structures, Automotive Aerodynamics & Vehicle Materials and Manufacturing.

Group Project – As a sustainability project, Investigated HVAC requirements for future vehicles, developing a methodology for assessment of current vehicles and applying those learnings to improve the design and identify potential areas of energy efficiency/harvesting aligned to future vehicle powertrains.

Thesis - Fast Charging Control of Electric Vehicle using Model Predictive Control (MATLAB & Simulink).

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