Matthew Guttenberg
Matt is a second year Ph.D. student under Venkat Viswanathan studying the dynamics of batteries as they relate to systems. He has been involved with numerous projects including how platooning, convoying of trucks, affects the energy requirements of electric semi-trucks, creating a charger placement algorithm called INCEPTS that hinges on the coupling of battery dynamics and vehicle dynamics as well as the locality of the simulation including weather, traffic flow, etc. Matt got his undergraduate degrees in Mechanical Engineering and Energy Engineering from the University of California at Berkeley and has had numerous internships in industry with companies such as SunPower.
Session
High-fidelity battery modeling requires the estimation of numerous physical parameters in order to properly capture the physics of the electrochemical, thermodynamic and chemical processes that underlie the system. Using Julia, the parameters for this model were able to be estimated by speeding up the code such that a Markov Chain Monte Carlo approach (Hamiltonian Monte Carlo) could be used, combined with a high-performance computing cluster, to sample the vast search domain and reach the global error minima.