Work Experience

I spent the summer of 2018 at the National Renewable Energy Lab with the Commercial Vehicle Technology Group. I was comparing in-use emissions of heavy duty vehicles to the emissions measured during certification testing. The goal was to ensure that the certification drive cycle was representative of in use driving from an emissions (NOx) perspective.

In use emissions data was limited for some vehicle types, but we did have GPS and CAN data for those vehicles (just no lab grade NOx data). I created a tool that estimated NOx emissions for the data sets that did not have sensor data by training a neural network on the data sets that we did have (scikit-learn in Python).

The result was a comparison of NOx emissions of in use drive cycles (g/kWh) to the emissions of the same vehicle during certification testing.

I worked at Inteva Products during the summer of 2017. I was a design engineer in the closures department (we designed car door latches and cinch actuators). Inteva is a Tier 1 supplier, meaning they work with OEMs (Ford, GM, Tesla) to produce parts for new vehicles. 

I was on an R&D team for electric vehicle components. Electric vehicle closure components are largely similar to those for fossil fuel vehicles, but are often designed to different NVH standards. We were working with a EV startup to create cinch actuators that fit the NVH profile of an electric vehicle, with a smoother and quieter operation.  

I took an existing design for a cinch actuator, stiffened the housing (in NX), and 3D printed several versions in carbon reinforced nylon. I then built a PLC driven test bench to cycle the actuators while monitoring acoustic performance and current draw. The design I initiated led to a final production model.

I learned a lot from this project, but looking back on it 4 years later, I wish I had known more about EMA and simulation. If I were doing it again, I would include modal analysis to reduce tonality peaks more effectively and test the prototypes in a controlled environment.

After graduating from high school I spent 6 months working at the Thomas E. Murphy Engine Research Lab. I was on a team that was using data from the suspension in metro busses to estimate passenger loads and per passenger emissions. 

We had been using NI cRIO systems to take data, but each logger cost several thousand dollars with the required hardware. We needed to outfit 20-30 busses with systems to log a GPS signal, the pressure in the air suspension, and signals from the CAN network (J1939). I specced and built Raspberry Pi based DAQs with all the required hardware inside a custom housing. I also programmed (Python) and assembled the DAQs.