Working on developing control algorithms for charging as a part of Lucid’s world-class Battery Management System

Thesis: Quantitative risk assessment and mitigation through fault diagnostics for automated vehicles.---I led a team of 20+ undergraduate and graduate engineering students at Ohio State to participate in General Motors - SAE AutoDrive Challenge II. I worked with the controls team to develop the planning and control software stack and integrate the same on the systems level with other hardware components. Additionally, I collaborated with the systems safety team to develop the overall pipeline for information flow considering the project requirements and safety standards for autonomous driving.

I worked with the Fault Analysis team on the full stack development of a prototype feature for performing fault tree analysis for the product: Simulink Fault Analyzer. The developed prototype allows users to create/edit fault trees with a GUI, perform exact failure probability calculations, and identify minimal cut sets. It is aimed to be used with Simulink to enable safety engineers to perform model-based fault tree analysis.

1. Collaborated towards developing the control framework for simulation and vehicle integration for Level 4 autonomy as a part of the SAE AutoDrive Challenge II, as the Co-lead for the planning & controls team. 2. Functioned as a co-captain to manage the interrelated deliverables from the perception, CAN, systems safety, and controls teams.

ME 3751: Kinematics and Mechanism Design | Dr. Haijun SuME 3670: Design and Analysis of Machine Elements I | Dr. Satyanarayana Seetharaman1. Responsible for conducting recitations, office hours and doubt clarification sessions for a batch of 60+ undergraduate students on a weekly basis

Development and testing of control algorithms for a prototype Hybrid Mobility Robot capable of rolling and flying in complex environments.------1. Modified the min. jerk trajectory planner for smooth navigation using a dynamic window of 3 waypoints per time step2. Formulated the cost-based path planning and obstacle avoidance approach using min. jerk planner and A* search algorithm3. Identified multiple methods to enable data-logging over cloud from the flight controller thus reducing manual intervention4. Assisted the technical team during the testing phase and analysing the test log.

Guide: Dr. Siddartha Khastgir | Antonio Bruto da Costa, PhD | Patrick Irvine |Verification & Validation team, Intelligent VehiclesRobust translation between 2 levels of Scenario Description Language for use in ADS simulation.---1. Developed the Java-based translation framework between levels of Scenario Description Language for ADS simulation2. Formulated the mapping between environmental features and language variables using the taxonomy from PAS 18833. Defined the boundary conditions for the agents’ maneuver to describe the Synchronised Serial Maneuver Sequences

Served as a mentor to tackle the technical as well as administrative challenges while assisting in planning for the upcoming season.

1. Budget and timeline preparation for design, manufacturing and participation in competitions.2. Responsible for leading a team of 47 enthusiasts towards the design and development of Formula Student electric/combustion prototypes. 3. Representative of the team to the professors, companies and the institute. 4. Ensured proper training of 1st and 2nd year students in technical as well as team management aspects despite pandemic-driven limitations. 5. Executed subsystem-specific design innovations for the overall progress of the team, while ensuring proper knowledge transfer to the juniors.

1. Represented the team in the Cost and Manufacturing Event at Formula Bharat 2020 and bagged the 15th position among 52 participating teams, in combustion category.2. Prepared the relevant Cost Report Documentations for the above-mentioned event.3. Collaborated in the complete powertrain design and assembly of a Formula Student combustion vehicle; represented the institute at Formula Bharat 2020 and competed with 52 Formula Student teams to get an overall 10th position. 4. Acquired monetary as well as technical sponsorships for the season 2019-20.5. Collaborated in the motor selection for a Formula Student Electric vehicle and calculated the optimized Final Drive Ratio of the same. 6. Designed the drivetrain setup comprising of planetary gearset, chain-sprocket drive and half-shafts. Performed the Static structural analysis to get the ideal FoS.7. FEA of differential mounts for the weight optimisation, keeping in mind the required FoS.8. FEA of half-shafts for the prototype to report its strength.

1. Fundamental knowledge about Internal Combustion Engine pertaining to the Formula Student competitions. a. Simulations for the design of the intake manifold for a given engine on Ricardo WAVE. b. CFD Simulations for the intake manifold based on specified boundary conditions. c. Turbocharger selection for a given engine, based on preset targets and other parameters. 2. Preliminary knowledge about drivetrain of an FSAE vehicle (consisting of components of power transfer from the engine to the wheels):- a. Final Drive Ratio Calculations (manual + software-based). b. Gear Strength Calculations (manual) and required simulation (on Ansys). c. Half-shaft design. d. Lap-time simulation for motor selection. e. Differential mount strength and FoS calculation through Ansys simulation.3. Manufacturing:- a. Basic training for the operation of power tools. b. Engine jig manufacturing.

1. Basic Vehicle Dynamics.2. CAD (using Solidworks).3. Mechanical Simulations (using Ansys)4. Public Relations Basics

Project title: Fault Tolerant Control System for Electric Vehicles [Bachelor's Thesis Project]Guide: Prof. Somnath Sengupta, Advanced Technology Development Center, IIT KGP.1. Multibody electric vehicle modelling with electromechanically integrated systems using Simulink and Simscape.2. Deployment of series brake blending strategy configured to recuperate max. energy during braking.3. Integration of Antilock braking system (ABS) and regenerative braking using tuned transfer function for ABS to track optimal wheel slip estimated dynamically using Buckhardt model.4. Analysis of the impact of faults on the vehicle's performance in terms of its stability.5. Implementation of an existing PI - sliding mode controller and identification of the limitations of the same.6. Development of a novel iterative constraint-aware controller by modifying the above scheme.7. Integration of a reconfigurable control allocation with the modified controller for fault-tolerant control.

Project Title: Mathematical Modeling of lithium-ion batteries with focus on Silicon anode particles.Guide: Dr. Jeevanjyoti Chakraborty, Mechanical Engineering Department, IIT KGP---1. Studied the mechanics behind crack development and formation of amorphous lithiated Silicon around the Silicon anode due to diffusion of Li+ ions2. Solved Ordinary as well as Partial differential equations, using Finite Difference and Liebmann’s methods, in Python3. Established a two-way coupling between diffusion and stress, to understand the effect of one parameter on the other.

Supervisor: Jeffrey P. Chrstos, PhD | Research ScientistPerformance assessment of Driver-in-the-loop simulators, specifically subsystem objective performance and analyzing and minimizing latency.

Mentors: Ravish Kumar | Rahul JainMemory footprint and inference time reduction for Deep Learning models using AI compilers and DL frameworks to efficiently deploy on edge devices for automotive applications.

Mentor: Dr. Naveen ArulselvanImplementation of G-mapping SLAM and exploration of Octomap mapping for autonomous cargo delivery vehicles using lidar point cloud and wheel odometry data.

Supervisors : Prof. Leena Vachhani & Prof. Arpita SinhaApplication of Machine Learning methods for motion planning of autonomous vehicles and comparison against Finite State Machine-based controller.

Projects: Autonomous Drone and Rover Prototype development, and automated agriculture