Recent automotive engineering graduate with 2 years of experience in developing control system algorithms for automotive/aerospace applications, generating models for dynamical systems, and model-based design.
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Experience
1. Intelligent Cruise Control for Highway using Fuzzy Encoded Markov Chains (FEMCs)
• Simulated randomly moving Lead car through Stochastic Modeling to generate a Control policy using Dynamic Programming.
• Performed Defuzzification of Control and Online learning of Transition Probability Matrix using FEMCs.
2. Mass Air Flow (MAF) Estimation for High Pressure EGR Flow
• Modeled flow through a nozzle and orifice to estimate transient EGR flow and corrected MAF estimates by adding Kalman Filter.
• Generated a calibrated model by creating fits for Cd (Discharge Coefficient), K̂ and achieved 1% error accuracy in EGR ratio.
3. Charging time estimation for Battery Electric Bus (BEB) transit system
• Estimated charging time variations for BEBs by developing SIMULINK models for Conventional, hybrid, battery electric buses & compared their mileage economies, CO2 levels.
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Projects
1. Integrated Adaptive Cruise Control using Model Predictive Control
• Developed an integrated MPC Control for Trajectory Following, Obstacle Avoidance, ACC.
• Used Waypoint Logic for Trajectory Following, Nearest Object Search for Obstacle Avoidance, and safe distance approach for ACC
2. Linear Feedback and Optimal Control
• Developed Quadratic Programming solver to generate MPC control actions for a mass-spring system with hard & soft constraints.
• Used Linear and Non Linear MPC to control spacecraft orientation to specified Euler angles using CasADi and MPCtools.
• Implemented LQR on Quarter Car Suspension to minimize tire deflections and designed Kalman Filter for an Inverted Pendulum.
• Designed Bang-Bang Control for minimum time control of a Double Integrator System using Hamiltonian & Phase Plane Analysis.
3. Adaptive Cruise Control (ACC) and Steering Control using Haptic Feedback
• Developed Adaptive Cruise Control (ACC) system using a vehicle model through control inputs of potentiometer and dip switches.
• Wrote C code to interface between vehicle model, NXPS32K144 microprocessor. Built Stateflow diagram to switch across 3 modes.
• Designed and tuned Cascade PD Control for Lane Centering while achieving speeds upto 60mph.
• Validated the model by identifying speeds & locations of other vehicles through CAN communication with CAN utilisation of 65%.
4. Hybrid Electric Vehicle Modeling and Power-Split Controller
• Developed a Conventional Ford F150 model with Modular 10 speed Automatic Transmission and hybridized it using P2 architecture
• Improved mileage by 35% using Rule based Controller with ECMS & implemented Torque Vectoring for better AWD capabilities.
5. Trajectory Optimization, Obstacle Avoidance
• Solved Non-Linear program using fmincon for driving a 6D car model with Pacejka's Magic Formula around F1 racetrack in 104s.
• Implemented PD Controller for Obstacle Avoidance (0 collisions) by applying Nearest Neighbor based Path Optimisation Algorithm
• Identified GPS coordinates and determined 3D motion through k-means clustering and SURF feature extraction.
6. Powertrain Controls
• Performed Air Fuel Ratio Control using manifold, puddle dynamics and used dynamic air charge estimator to compensate sensor lag
• Performed Idle speed control by utilising built-in Simulink engine model.
7. Engine Heat Waste Recovery, General Motors (Multi - Disciplinary Design Project)
• Lead a team of 6 students and provided recommendations to GM by implementing engine heat waste recovery techniques.
• Developed 3.6L LFX engine model using GT Suite & generated maps from it by varying bmep to run the vehicle model in GT-Suite
• Optimised fuel efficiency improvement for Rankine Cycle Waste Heat Recovery (WHR) & swept across various WHR parameters.