Pre-Feature Owner (Systems Engineering) at FORD Motor Company
 Designed and developed various features, while working with cross-functional teams.
 Lead various features into successful production vehicles, and presented a clinic with customers.
Systems Feature 1:
 Designed and developed the basic outline of the feature involving infotainment systems and displays, that involves artificial intelligence and 3D images, and would further collaborate with ADAS technologies.
Systems Feature 2 (Electrical Systems Lead):
 Designed and developed an innovative feature that involves various mechanical and electrical components of the driving module, steering column, ECU’s Battery, Motors, Controls software like Arduino, MATLAB, Simulink, Stateflow.
 Designed and developed a new Electronic Control Module (ECU/ECM) for a vehicle, that involves motors (DC, stepper), microcontroller (Arduino) and embedded software technologies like Arduino, MATLAB, Simulink, Stateflow.
 Developed and build a clinic for this feature, to showcase its abilities to the customer, and review feedback.
Systems Feature 3 (Feature Modeling Lead):
 Designed and developed a system model using MATLAB, Simulink, and MagicDraw, which is the thermal optimization strategy for the vehicle cabin temperature, while working with more than 12 cross-functional teams.
Systems Feature 4 (Feature Lead):
 Designed and developed a feature that involves various components like chassis, a trailer hitch, axle, wheels, and the infotainment systems (Ford SYNC module), and CAN data.
 Designed the boundary diagram, Stateflow and sequence diagrams using MagicDraw (SysML) and Visio, and analyzed the requirements, cost, and resources needed for the feature and document it using MagicDraw feature documentation.
 Analyzed the functional safety issues using the FMEA process and presented the required FMA documents.

Wireless Sensor Network (WSN) Architecture for Intelligent Transportation Systems with Software Defined Networking (SDN): Designed a new architecture of WSN based on SDN for ITS (connected vehicles), which is comparably advantageous to other traditional architectures.
Design of a configurable hybrid electric learning modules (CHELM); Design of different modules required: Sensor, actuator, and control modules.
Includes different control logic models: Engine state logic, Torque/Throttle request, Engine start/stop, Electric motor start/stop, and stepper motor driving models.
Obtained smooth transition between different engine states, based on various driving conditions.
Design of a digital controller for an Electronic Throttle Body (Bosch): Developed a feedback position control system for an ETC using a discrete controller (to control the opening of the throttle body based on pedal position).
Routing Solution for Connected Automated Vehicles (RCAV): Designed an algorithm-based system for attaining the shortest path possible based on different traffic scenarios and congestion control.
Electronic Throttle Control – Digital Controller and CAN (remote): Developing a digital controller using a PID controller to control the opening of the throttle body based on received commands and establishing communication between ECU’s using CAN.
Design of a Fuel Injection Controller: Actuated a Fuel Injector using simulated engine data and designed a temperature compensation model to improve the fuel injection control.
Design of a Hybrid Electric Vehicle (HEV) Powertrain Controller: Developed a Model-based powertrain controller for a series-parallel HEV using Stateflow in MATLAB.
Autonomous Car Parking: Implementation of the functioning of the autonomous car parking system using a multi-chassis (for a car model), the motor shield as an engine, and the ultrasonic sensor as a ranging sensor.
Design of an Idle Speed Controller: Developed a non-linear engine model based on a PID controller to vary the spark timing and throttle position at a constant speed.
Design of an Intelligent Cruise Control system: Developed a PI controller to cruise at the desired speed and a steady-state LQR to maintain headway from the lead vehicle.
Dynamic Programming and Model Predictive Control: Developed algorithms using DP and MPC techniques to minimize the cost function of a system.
Obstacle Detection of Nodes: To steer the DC motor by the potentiometer and an ultrasonic sensor, if the obstacle is detected at a certain distance, or else the speed will be reduced gradually and halts irrespective of the potentiometer position.
Controlling the direction of Multi-Chassis using H-Bridge: Controlling the direction of a multi-chassis (representing a vehicle body) based on Arduino.
DC motor and Servo motor control: To control the DC motor and the servo motor with respect to the accelerometer position, based on angular and linear position.