Patents by Inventor Mumtaz Vauhkonen

Mumtaz Vauhkonen 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).

  • Tire wear estimation using a hybrid machine learning system and method
    Patent number: 10960712
    Abstract: A tire tread wear system may include one or more vehicle sensors and a processor. The processor may include a control module, a geometrical model, a machine learning model, and a switch. The geometrical model may be configured to collect data from the vehicle sensors to determine a dynamic rolling radius of a tire. The geometrical model may be configured to output a tread wear estimation based on the dynamic rolling radius of the tire. The machine learning model may be configured to collect data from the vehicle sensors. The machine learning model may be configured to output a tread wear estimation based on a correlation of the tread wear estimation output from the geometrical model and one or more data instances with a tire tread state. The switch may be configured to activate the geometrical model, the machine learning model, or a combination thereof.
    Type: Grant
    Filed: June 28, 2018
    Date of Patent: March 30, 2021
    Assignee: Nissan North America, Inc.
    Inventors: Gian Luca Storti, Mumtaz Vauhkonen, Gregory D. Dibb
  • Tire Wear Estimation Using a Hybrid Machine Learning System and Method
    Publication number: 20200001662
    Abstract: A tire tread wear system may include one or more vehicle sensors and a processor. The processor may include a control module, a geometrical model, a machine learning model, and a switch. The geometrical model may be configured to collect data from the vehicle sensors to determine a dynamic rolling radius of a tire. The geometrical model may be configured to output a tread wear estimation based on the dynamic rolling radius of the tire. The machine learning model may be configured to collect data from the vehicle sensors. The machine learning model may be configured to output a tread wear estimation based on a correlation of the tread wear estimation output from the geometrical model and one or more data instances with a tire tread state. The switch may be configured to activate the geometrical model, the machine learning model, or a combination thereof.
    Type: Application
    Filed: June 28, 2018
    Publication date: January 2, 2020
    Inventors: Gian Luca Storti, Mumtaz Vauhkonen, Gregory D. Dibb