• Lead Rivian R1 and EDV (Amazon Delivery Van) Adaptive Cruise Control (ACC) motion planning and controls stack from prototype to production level

• Developed longitudinal speed planning and controls algorithm for full speed range ACC w.r.t. selected object including automatic acceleration/deceleration, driver interaction with gap and speed selection, accelerator pedal override, and feature engagement

• Designed scalable and calibratable ACC algorithms following ISO26262 for different dimensions of vehicles including R1T, R1S, and EDV

• Designed and conducted ACC testing scenarios including full speed cut-in/cut-out, mid and low speed stop and go, full speed full stop on stationary object, and driver intervened tests on both closed track and open public road

• Validated the ACC speed planning and controls stack via unit tests with Parasoft, Model in loop (MiL) test, simulation with AV simulation SCANeR, and vehicle tests

• Developed ACC Key Performance Index (KPI) on standardized test scenarios evaluating the vehicle longitudinal performance against different software releases

• Established data visualization scripts for ACC tests including standardized test scenarios and on-road tests

• Developed component-level requirements (T3) for Adaptive Cruise Control with the requirement management system (JAMA)

• Architecture and Software Controls Team

Project: Software Development: Climate Control Unit (Prototyping Controller)

• Built the EV Climate Control Unit application software from scratch and achieved the multi-zone temperature controls function

• Function owner of the multi-zone temperature control, EXV control, PTC control, blower control, and mode door control

• Designed the control algorithm for the multi-zone cabin temperature control including cooling, heating, and ventilation function with the HVAC system using the rapid prototyping controller (dSpace MicroAutoBox)

• Applied classical feedback control such as PID to the controller and established the design of the experiment (DOE) for the feedforward look-up table

• Established the controller target setting estimation and calibrated via vehicle testing

• Implemented the model-based control software of the climate control unit (CCU) for the electric vehicles

• Established the HVAC system simulation model for electric vehicles with the system identification technique

• Tuned the controller gain and analyzed the system based on the identified transfer function of the system

• Developed the system-level requirements for the climate control unit of the electric vehicles with the requirement management system (JAMA) by modifying the existing climate control requirements

• Validated the control system via unit testing, model-in-the-loop (MIL) testing, and vehicle testing (via DAQ such as Vector CANoe and dSpace ControlDesk) based on the system and technical requirements

• Established the time-series data visualization script for the controller performance and the control system calibration