Li Zhang
About
Li Zhang is from Palo Alto, California, United States. Li works in the following industries: "Automotive". Li is currently Engineering Manager at Tesla, located in Palo Alto, California, United States. In Li's previous role as a Staff Engineer at Tesla, Li worked in Palo Alto until Aug 2020. Prior to joining Tesla, Li was a Senior Architecture and Modeling Engineer at Tesla and held the position of Senior Architecture and Modeling Engineer at San Francisco Bay Area. Prior to that, Li was a Graduate Student Researcher at Advanced Power and Energy Program, based in University of California, Irvine from Sep 2009 to Jun 2014. Li started working as Internship at Toyota ITC in Mountain View, California in Nov 2013. From Aug 2010 to Aug 2010, Li was Student Researcher at Horiba, based in Ann Arbor, MI. Prior to that, Li was a Undergraduate Student Researcher at Universidad Politécnica de Madrid, based in Madrid Area, Spain from Mar 2009 to Jul 2009.
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Li Zhang's current jobs
Lead the Charging Data and Modeling team at Tesla. • We measure the usage of the charging network with charging KPIs. • We model the charging behavior and the network with physical simulations, machine learning techniques and engineering intuitions. • We optimize the charging network with the lowest cost to Tesla and the highest utility to our customers.
Li Zhang's past jobs
• Led the capacity planning effort for Tesla's Supercharger network. • Led the modeling work of the time-of-use price implemented on Tesla's Supercharger network. Oversaw the implementation of the optimization based microgrid dispatch algorithm. • Led the product economic analysis and system sizing for the next generation Powerwall. • Led the design and implementation of the control mechanism embedded on the energy gateway used for Tesla's virtual power plant. • Led the online battery dispatch algorithm design, modeling, implementation and the performance benchmarking for the time-based-control (TBC) feature on Tesla Powerwall.
• Led the modeling work on sizing Tesla's Gen 3 Supercharger and its economics. • Led the development of the simulation tool used for sales purposes for Tesla Powerpacks. • Led the development of the realtime control strategy for executing the peak shaving command. • Led the development of Opticaster, Tesla's MPC based control algorithm used for Powerpacks at all the Tesla's C&I projects. The primary features implemented include demand and solar forecast, peak shaving, energy arbitrage, ITC compliance, SGIP incentive maximization, demand response, special pricing and battery degradation mitigation.
Evaluated PHEV energy consumption with different ranges and charging scenarios. Optimized Level 1 and Level 2 charging infrastructure for different location categories in California. Optimized the allocation of the Level 3 DC fast charging stations in California. Collaborated with government agencies (the California Energy Commission) and major automakers (Toyota and Honda) to apply research findings above to real-world settings.
Proposed an effective control mechanism for a large amount of EVs in a region to achieve demand leveling, i.e. minimize charging impact on the grid, for the future EVs.
Formulated PHEV dynamometer test plan on the Plug-in Prius, Coordinated with Horiba Automotive Division staff to conduct the actual tests, analyzed data and published papers.
Worked in the university’s automotive center on a series HEV model functioned as a used battery recycling vehicle and completed thesis on the model simulation.