Patents by Inventor Benben Jiang

Benben Jiang has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Systems and methods for predicting battery life using data from a diagnostic cycle
    Patent number: 11768249
    Abstract: System, methods, and other embodiments described herein relate to improving the estimation of battery life. In one embodiment, a method includes measuring electrochemical data of a battery cell associated with an electrochemical reaction triggered by a test during a diagnostic cycle. The method also includes determining a feature associated with the degradation of the battery cell from the electrochemical data. The method also includes predicting an end-of-life (EOL) of the battery cell by using the feature in a machine learning (ML) model.
    Type: Grant
    Filed: March 31, 2021
    Date of Patent: September 26, 2023
    Assignees: Toyota Research Institute, Inc., Massachusetts Institute of Technology, The Board of Trustees of the Leland Stanford Junior University
    Inventors: William C. Chueh, Bruis van Vlijmen, William E. Gent, Vivek Lam, Patrick K. Herring, Chirranjeevi Balaji Gopal, Patrick A. Asinger, Benben Jiang, Richard Dean Braatz, Xiao Cui, Gabriel B. Crane
  • Systems and methods for predicting the cycle life of cycling protocols
    Patent number: 11614491
    Abstract: System, methods, and other embodiments described herein relate to improving the cycling of batteries by using data and a hierarchical Bayesian model (HBM) for predicting the cycle life of a cycling protocol. In one embodiment, a method includes classifying cycle life of a battery into a class using battery data from cycling with a protocol, wherein the class represents cycle life distributions of cycling protocols. The method also includes quantifying, using the class in a HBM, variability for the battery induced by the protocol. The method also includes predicting, using the HBM, an adjusted cycle life for the protocol according to the variability. The method also includes communicating the adjusted cycle life to operate the battery.
    Type: Grant
    Filed: April 20, 2021
    Date of Patent: March 28, 2023
    Assignees: Toyota Research Institute, Inc., Massachusetts Institute of Technology, The Board of Trustees of the Leland Stanford Junior University
    Inventors: Richard Dean Braatz, Benben Jiang, Fabian Mohr, Michael Forsuelo, William E. Gent, Patrick K. Herring, William C. Chueh, Stephen J. Harris
  • SYSTEMS AND METHODS FOR PREDICTING THE CYCLE LIFE OF CYCLING PROTOCOLS
    Publication number: 20220341995
    Abstract: System, methods, and other embodiments described herein relate to improving the cycling of batteries by using data and a hierarchical Bayesian model (HBM) for predicting the cycle life of a cycling protocol. In one embodiment, a method includes classifying cycle life of a battery into a class using battery data from cycling with a protocol, wherein the class represents cycle life distributions of cycling protocols. The method also includes quantifying, using the class in a HBM, variability for the battery induced by the protocol. The method also includes predicting, using the HBM, an adjusted cycle life for the protocol according to the variability. The method also includes communicating the adjusted cycle life to operate the battery.
    Type: Application
    Filed: April 20, 2021
    Publication date: October 27, 2022
    Applicants: Toyota Research Institute, Inc., The Board of Trustees of the Leland Stanford Junior University, Massachusetts Institute of Technology
    Inventors: Richard Dean Braatz, Benben Jiang, Fabian Mohr, Michael Forsuelo, William E. Gent, Patrick K. Herring, William C. Chueh, Stephen J. Harris
  • SYSTEMS AND METHODS FOR PREDICTING BATTERY LIFE USING DATA FROM A DIAGNOSTIC CYCLE
    Publication number: 20220137149
    Abstract: System, methods, and other embodiments described herein relate to improving the estimation of battery life. In one embodiment, a method includes measuring electrochemical data of a battery cell associated with an electrochemical reaction triggered by a test during a diagnostic cycle. The method also includes determining a feature associated with the degradation of the battery cell from the electrochemical data. The method also includes predicting an end-of-life (EOL) of the battery cell by using the feature in a machine learning (ML) model.
    Type: Application
    Filed: March 31, 2021
    Publication date: May 5, 2022
    Applicants: Toyota Research Institute, Inc., The Board of Trustees of the Leland Stanford Junior University, Massachusetts Institute of Technology
    Inventors: William C. Chueh, Bruis van Vlijmen, William E. Gent, Vivek Lam, Patrick K. Herring, Chirranjeevi Balaji Gopal, Patrick A. Asinger, Benben Jiang, Richard Dean Braatz, Xiao Cui, Gabriel B. Crane