Patents by Inventor Sriram Jayachandran Raguraman

Sriram Jayachandran Raguraman 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).

  • Intelligent mass air flow (MAF) prediction system with neural network
    Patent number: 11840974
    Abstract: The Method and Apparatus of Predicting MAF Sensor Information includes training multiple candidate Artificial Neural Network (ANN) architectures using training data, and then selecting an ANN architecture from the candidates using an automated ANN architecture selection algorithm and testing data. An intelligent engine intake MAF prediction or estimation system using the selected ANN architecture then provides an engine intake Mass Air Flow (MAF) output variable, which is used along with the output of a hot-wire type engine intake MAF sensor. The system is deployed into the engine controller. The training and testing sets of data include input variables from engine sensors and/or actuators that relate to engine intake MAF, and may be acquired by testing a target engine. Selecting the optimal ANN architecture may be based on Root Mean Squared Error (RMSE) analysis using the automated ANN architecture algorithm and the training set of data.
    Type: Grant
    Filed: April 30, 2021
    Date of Patent: December 12, 2023
    Assignee: International Engine Intellectual Property Company, LLC
    Inventors: Askin Minaz, Ravi Rayala, Jungme Park, Rahul Rajampeta Rahul Rajampeta, Manoj Vemuri, Sriram Jayachandran Raguraman
  • Intelligent Mass Air Flow (MAF) Prediction System with Neural Network
    Publication number: 20220349358
    Abstract: The Method and Apparatus of Predicting MAF Sensor Information includes training multiple candidate Artificial Neural Network (ANN) architectures using training data, and then selecting an ANN architecture from the candidates using an automated ANN architecture selection algorithm and testing data. An intelligent engine intake MAF prediction or estimation system using the selected ANN architecture then provides an engine intake Mass Air Flow (MAF) output variable, which is used along with the output of a hot-wire type engine intake MAF sensor. The system is deployed into the engine controller. The training and testing sets of data include input variables from engine sensors and/or actuators that relate to engine intake MAF, and may be acquired by testing a target engine. Selecting the optimal ANN architecture may be based on Root Mean Squared Error (RMSE) analysis using the automated ANN architecture algorithm and the training set of data.
    Type: Application
    Filed: April 30, 2021
    Publication date: November 3, 2022
    Applicant: International Engine Intellectual Property Company, LLC
    Inventors: Askin Minaz, Ravi Rayala, Jungme Park, Rahul Rajampeta Rahul Rajampeta, Manoj Vemuri, Sriram Jayachandran Raguraman