Working as Senior Product Engineer in the Semi Truck team

(Dec 23-)

1. Leading the effort to mitigate and tackle current challenges in Semi Truck

2. Addressing the feature enhancement via driver's feedback

3. Use fleet analytics to regulate and monitor fleet-wide concerns

4. Collaborate with various engineering teams to perform field quality checks for establishing the root cause and failure/corrective analysis.

5. Perform DFMEA to establish the path to success in future products.

Cell Engineering and Mechanical Modeling intern

(Jan 22-Aug22)

Battery Modeling and Technology Division: Lifetime forecasting, Mechanical modeling and Data analytics intern

1. Battery design of Tesla Bot

   1. 1. 1. 1. Executed semi-empirical modeling to forecast battery life of Tesla Bot considering charging and discharging.

            2. Partnered with the Mechanical Design team to optimize the robot’s thermal performance based on operation time, State of Charge (SoC), and Depth of Discharge (DoD) of the battery.

2. Cell Lifetime forecasting

   1. 1. 1. 1. Matured statistical physics model for forecasting lifetime of vendor cells across multiple form factors of 1865/2170/4680 to be used in Tesla Model 3 and Model Y.

            2. Implemented least-square nonlinear algorithm using MATLAB for modeling modified Arrhenius loss equation to analyze energy decay and capacity loss of a cell.

            3. Worked in collaboration with Cell Characterization and Cell Qualification Labs to develop a visualization tool for Lithium Iron Phosphate (LFP) cells.

3. Statistical analysis to calculate error &  confidence in forecasting model & identification of failure point

   1. 1. 1. 1. Improved the performance and working of pre-existing lifetime models by analyzing datasets with over a million entries and by introducing statistical errors and confidence intervals.

            2. Proposed and implemented a method to benchmark the cycle life of a cell, based on 610 different cells.

            3. Designed a slope tracing algorithm to identify a sudden change in cell capacity thereby letting the experimental team know about the throughput cutoff point.

            4. Introduced statistical failure points for different cell types, forecasting battery packs replacement time.

4. Mechanical modeling and validation

   1. 1. 1. 1. Performed material card validations using commercial FEA software, such as ABAQUS and LS-DYNA

            2. Developed ABAQUS post processing tool by scripting with MATLAB and Python enabling the study of cell mechanical simulation results

            3. Validated the cell mechanical models using the high-resolution CT image data

            4. Assisted the mechanical lab tests and developed MATLAB scripts for post-processing raw test data

5. Powerwall and Megapack reliability

   1. 1. 1. 1. Ensured 70% post-test capacity retention checks for vendor cells under High-Temperature Humidity Endurance (HTHE) and Powered Thermal Cycling Endurance (PTCE) conditions. 

            2. Forecasted Megapack lifetime based on extreme weather conditions ensuring selection of correct chemistry for the proposed class of vendor cells.

6. Inhouse cell development

   1. 1. 1. 1. Built a framework to analyze the lifespan of Tesla’s high energy density inhouse cells to be used in Power Wall, Cyber Truck, and Semi.

            2. Teamed with Tesla’s cell manufacturing facility at Kato, California to develop a control protocol for charging and discharging test and source cells for various State of Charge (SoC).

Supervisor: Professor Dmitry. V. Feoktistov, Department of theoretical and industrial heating equipment

• Modeled working of closed vertical thermosiphon computationally using ANSYS (FLUENT) 18.0.

• Structured flow for various fill-in ratio and heat fluxes, optimizing the efficiency of the experimental model

• Amassed working principles of heat exchangers in parallel flow, cross flow, and counter flows

• Analyzed numerical data and grasped concept of heat profile and turbulent mixing between multi-phase flows

• Coordinated with industry personnel towards data collection of heat transfer across liquor tanks

The work can be read here