Patents by Inventor Naveed ARSHAD

Naveed ARSHAD 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).

  • Method and system for predicting battery capacity degradation for electric vehicle
    Patent number: 12623570
    Abstract: A method and a system for predicting a battery capacity degradation for an electric vehicle having a battery are provided. The method comprises extracting and pre-processing a raw dataset comprising a plurality of battery loss indicators and a plurality of battery loss values each corresponding to a plurality of time steps to obtain a pre-processed dataset. The method further comprises selecting a loss indicator subset from the pre-processed dataset at a first time step and a second time step based on a smart feature selection (SFS) algorithm. The method further comprises training a machine learning model with each battery loss indicator at the first and second time steps and the battery loss value at the first time step. The method further comprises determining the battery loss value at the second time step with the machine learning model to predict the battery capacity degradation.
    Type: Grant
    Filed: May 7, 2024
    Date of Patent: May 12, 2026
    Assignee: KING FAHD UNIVERSITY OF PETROLEUM AND MINERALS
    Inventors: Muhammad Khalid, Huzaifa Rauf, Naveed Arshad
  • METHOD AND SYSTEM FOR PREDICTING BATTERY CAPACITY DEGRADATION FOR ELECTRIC VEHICLE
    Publication number: 20250346150
    Abstract: A method and a system for predicting a battery capacity degradation for an electric vehicle having a battery are provided. The method comprises extracting and pre-processing a raw dataset comprising a plurality of battery loss indicators and a plurality of battery loss values each corresponding to a plurality of time steps to obtain a pre-processed dataset. The method further comprises selecting a loss indicator subset from the pre-processed dataset at a first time step and a second time step based on a smart feature selection (SFS) algorithm. The method further comprises training a machine learning model with each battery loss indicator at the first and second time steps and the battery loss value at the first time step. The method further comprises determining the battery loss value at the second time step with the machine learning model to predict the battery capacity degradation.
    Type: Application
    Filed: May 7, 2024
    Publication date: November 13, 2025
    Applicant: KING FAHD UNIVERSITY OF PETROLEUM AND MINERALS
    Inventors: Muhammad KHALID, Huzaifa RAUF, Naveed ARSHAD