Pranav Salunke

https://www.linkedin.com/in/pranav-salunke-1a994b75/

**** **** ****** **., *** 4010 Cell: 906-***-**** Troy, MI 48084 Email: ac1dmn@r.postjobfree.com

OBJECTIVE

To obtain a full time position in the field of Mechanical/Automotive Engineering (EAD Received). EDUCATION

Michigan Technological University, Houghton, MI, USA Graduated April 29th, 2017 MS Mechanical Engineering Overall GPA: 3.93 out of 4 University of Pune, Pune, MH, India Graduated May 2015 BE Mechanical Engineering Overall GPA: 3.23 out of 4 RELEVANT ENGINEERING EXPERIENCE

Autonomous Control and Navigation of a Lab-Scale Mining Haul Truck Advisor Dr. Mohsen Azizi, Aug - April 2017 1. This project focuses on autonomous control of a small lab-scale truck using LiDAR sensor. The main goal is to make this truck autonomous and capable of finding its path along the simulated underground mining route. 2. The dynamic equations of the truck were calculated and simulated using Simulink for designing the control algorithm which is based on a PID controller and a multiple-point path tracking approach. 3. A LiDAR system is used as a sensor for measurement, and a navigation algorithm is developed in Python based on triangulation of the measurement data from the LiDAR sensor to estimate the truck position. 4. Raspberry Pi microcontroller is used to control the truck to which the navigation and control algorithms, developed in Python, are implemented.

Automotive Control Systems Course Instructor Dr. Jeffery Burl, Aug - Dec 2016 1. Successfully completed simulation projects on Intelligent Cruise Control Design, designing optimal LQR control of SI engine idle speed using integral control and calibration of PID controller of a Torque Converter Lockup Clutch system in an automobile.

Remote electronic throttle control via CAN communication Instructor Dr. Bo Chen, Feb - March 2016 1. Developed a remote electronic throttle control system in Simulink via CAN communication using a Bosch DV-E5 throttle (ETB), two ECM 565-128, MotoTron rapid prototyping systems and CAN Hardware tools. 2. Used an optimally tuned PID in the model to control the PWM signals to the ETB, based on the input signal of the accelerator pedal position sensors and feedback of throttle position sensors. 3. Validation of the model was done by observing the steady state and transient response of the ETB in real time. Hybrid Electric Vehicle Enterprise (Sponsored by GM) Advisor Dr. Robert Page, Jan - May 2016 1. Developed control logic for HV battery system using Simulink/Stateflow with CAN messages from CANoe and also built AmeSim model of battery, inverter and E-motor for simulation purposes. 2. Achieved complete automation of Tremac T5 manual transmission using stepper motor and linear actuator whose control logic was developed in Simulink and exported to dSPACE supervisory controller. Balance of a two wheeled inverted pendulum robot Advisor Dr. Nina Mahmoudian (NAS Lab), Sep - Dec 2015 1. Calculated the state model of the system and simulated the model using PID controller in Matlab. 2. Tested controller on a prototype robot using Beaglebone Black processor, accelerometer and gyroscopic sensor. COMPUTER/TECHNICAL SKILLS

Proficient: MATLAB, Simulink, LabVIEW, Stateflow, dSpace, HIL Simulation, RSLogix, MotoTune, ProE, MS office Good: C/C++, Python, AutoCAD, AmeSim, CANoe, CANKing CO-CURRICULAR INVOLVEMENT

1. American Society of Mechanical Engineering (ASME), Michigan Technological University 2. Robotics Cell Member Mechanical Engineering Students Association (MESA), PVG’s COET, Pune, India RELEVANT COURSES

Automotive Control Systems, Feedback Control of Dynamic Systems, Digital and Non-linear Control, Distributed Embedded Control System, Multi-agent Simulation of Dynamic Systems, Analytical Vibroacoustics