Automotive Systems Enginerer, Mechatronics Engineering

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Dearborn, MI, 48126 http://www.linkedin.com/in/arunjoshi088 *****@*****.*** Summary

• Automotive systems engineering graduate student with Mechatronics Engineering background through bachelor’s degree.

• Area of interest includes ADAS, Autonomous Vehicles (AV) and Robotics, Vehicle Dynamics, Stability and Controls, Digital Control Systems and Embedded Systems

• Experience in MATLAB/Simulink for 3+ years with works that involve creating mathematical models for systems/vehicle and implementing control algorithms that facilitate stability control for vehicles and running co-simulation with Prescan to implement ADAS features using virtual sensors like Lidar/Monocular camera based AEB and Lane Keep Assist (LKA).

• Experience in Robotic Operating System (ROS) and Linux with Python and C/C++ based coding using Pycharm/ Eclipse IDE for 1+ years creating ROS nodes, topics and custom message types along with embedded systems, basics of Computer Vision and Convolutional neural network for object detection

• General understanding of communication protocols such as CAN, SPI and I2C

• Knowledge in classical control theory – PID, root locus method to identify pole-zero location and Bode Plot analysis along with understanding of concepts like Kalman filter, Extended Kalman Filter and Model Predictive Controller

• Ability to adapt and passionate to learn and implement new technologies that challenges the existing methodologies.

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Key Skills

MATLAB Simulink LabVIEW PreScan TruckSim Python C/C++ Robotic Operating System (ROS) Linux SolidWorks Catia Solid Edge Sketchup MS Office Proteus Kiel PLC SCADA Education

MSE in Automotive Systems Engineering from University of Michigan Dearborn (2017-2019) GPA:3.63/4.0 Relevant Courses: Vehicle Dynamics, Vehicle Stability and Control, Digital Control Systems, Integration of Vehicles, IC Engines

Dearborn, MI

BE in Mechatronics Engineering from Visvesvaraya Technological University (2012-2016) GPA:3.91/4.0 Relevant Courses: Automotive Electronics, Embedded Systems, Microcontroller and Microprocessors, Programming - C/C++/Python/embedded C, Digital Signal Processing, Control Theory Bangalore, India

Advanced PG Diploma in Embedded Systems and Industrial Automation from SMEC LABS Bangalore, India Work Experience

Graduate Research Assistant, University of Michigan-Dearborn January 2019-present

• Created a custom animator model for TruckSim that can be used to visualize the vehicle under consideration and tested various stability scenario to prove its validity for the study conducted by vehicle Dynamics and Simulation Lab.

• Supervised Undergraduate senior design team in their project and provided technical reviews on their design and execution.

Graduate Student Instructor and Teaching Assistant, University of Michigan-Dearborn May 2018-present

• Worked as Lab Instructor for Control Systems design and Analysis course offered for undergraduate students in ME Dept. covering topics such as PID controller, root locus method for zero and pole selection and Bode Plot analysis.

• Worked as a grader for the coursework and assignments of ME-543 (Vehicle Dynamics) course offered for graduate students.

Intern, Origin D-FAB PVT LTD., Bangalore, India January 2016 – April 2016

• Benchmarking on Additive Manufacturing technology involving rapid prototyping using DMLS

• Design a feasible concept for the traverse mechanism for metal powder hopper used in DMLS using Solidworks Academic Projects

HIL-Simulation and Validation tool for Vision based ADAS system using vehicle scale model, University of Michigan-Dearborn, 2018 - present

• Tested vision based ADAS with camera as a hardware in the loop (HIL) configuration with Simulink to detect vehicles and distance to obstacle

• The front view of vehicle is virtually generated using Prescan and captured live in real time to identify the vehicle ahead and range to obstacle using a Convolutional Neural Network (R-CNN).

• Developed a scale model prototype that is equipped with relevant sensors to test out the control algorithm that can execute AEB and lane change using data from vision sensor and other ADAS enabling systems.

• Simulation is done in Matlab with Prescan software in Loop along with hardware mimicking the vehicle behaviour

• The prototype interfacing is done using Robotic Operating System in Linux (ubuntu 16.04) and Simulink (Robotic System toolbox and Automated driving toolbox) to run independently as well as to run along with Prescan simulation.

• Developed ROS nodes hardcoded using Python and C++ following object-oriented programming for executing control algorithms independently as well as using Matlab coder for converting Matlab/Simulink code into independent ROS node Vehicle Yaw Moment Control Using Fuzzy Logic Control, University of Michigan-Dearborn, 2018

• An 8-DOF vehicle model was created using Simulink to observe the dynamics of the vehicle with Dugoff tire model for the generation of tire forces and is incorporated to the vehicle model.

• For reference, a linear 2 DOF vehicle model is used to compute desired yaw rate and the side slip angle is maintained to zero.

• For actuation, differential braking method is followed, and the fuzzy logic controller is implemented to achieve the control law and provide the corrective yaw moment.

• Output trajectory, change in Side slip and yaw rate are observed and compared in Simulink to see the effectiveness of the controller on scenario like single lane change and J-turn as steering input Bicycle lean Angle Control, University of Michigan- Dearborn, 2018

• Implemented a self-balancing bicycle using steering actuation to counter roll and lateral acceleration.

• A model-based approach was performed in Matlab to observe the balancing using a full state feedback controller

• A Pyboard and DC motor along with an H-bridge controller is utilized to achieve the steering actuation.

• Developed a PI control and implemented it to the hardware that modulates the duty cycle of PWM based on error.

• Incorporated the bicycle in the loop & further calibrating the PI controller and the bicycle self-balanced for 50 feet in a no rider-initial push condition.

Autonomous Emergency Braking System, University of Michigan-Dearborn, 2018

• Utilized Simulink to model the AEB system along with a vehicle model. Used Arduino and Ultrasonic sensor as HIL to emulate the radar in the system and fed the signal to Simulink in real time as input to enable the braking system.

• Low pass filter is used to reduce the noise and smoothen the sensor signal output.

• 3 stage braking is used to apply different percentage of braking pressure based on range to the obstacle

• Created a DFMEA for the Autonomous Emergency braking system. Benchmarking, Functional specifications, Business development plan for Model year 2023 vehicle, University of Michigan- Dearborn, 2018

• Benchmarked the selected reference vehicle with its competitors. Utilized a KANO model and PUGH chart to aid in preliminary specifications and design decisions.

• For the climate control system an Interface matrix & diagram was created. The functional specifications were also developed using Quality Function Deployment (QFD) and cascaded the vehicle attributes to system requirements.

• Gathered data and created a business development plan for the model year 2023 vehicle Honors & Awards

• Graduate Student Independent Research Grant – University of Michigan-Dearborn- 2019

• Non-Resident Graduate Student Scholarship - University of Michigan-Dearborn, 2017/19

• University 4th rank holder in Mechatronics Engineering – Visvesvaraya Technological University, 2012-2016

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