Abstract: This disclosure relates generally to a method and system for real time monitoring and forecasting of fouling of an air preheater (APH) in a thermal power plant. The system is deploying a digital replica or digital twin that works in tandem with the real APH of the thermal power plant. The system receives real-time data from one or more sources and provides real-time soft sensing of intrinsic parameters as well as that of health, fouling related parameters of APH. The system is also configured to diagnose the current class of fouling regime and the reasons behind a specific class of fouling regime of the APH. The system is also configured to be used as advisory system that alerts and recommends corrective actions in terms of either APH parameters or parameters controlled through other equipment such as selective catalytic reduction or boiler or changes in operation or design.

Abstract: The efficient operation of an electric vehicle depends greatly on proper functioning of a battery pack in the electric vehicle. A system and method for optimizing the operation of the battery pack in an electric vehicle is provided. The system comprises a digital twin for a battery pack in an electric vehicle. The system determines the state of charge, state of health and temperature distribution in the battery pack using various models. This information can be used to predict optimal charge and discharge profiles of the battery pack for given load conditions, as well as remaining useful life of the battery. The digital twin would require inputs such as battery temperatures from the sensors, coolant flow rates, coolant temperature, ambient temperature, load on the vehicle, current and voltages from the pack and battery characteristics from the manufacturer.

Abstract: Performance and lifespan of batteries deteriorate with time due to various factors. Existing systems for battery management use different approaches for the battery management, and also rely on static value of parameters for State of Health (SOH) and Remaining Useful Life (RUL) estimation, thereby failing to consider current condition of the battery. The disclosure herein generally relates to battery management, and, more particularly, to a method and system for online battery management involving real-time estimation of State of Health (SOH) and Remaining Useful Life (RUL) of a battery, based on real-time data collected from the battery. The system determines state of the battery as one of charging, discharging, and rest. Further, corresponding to the determined state, the system determines values of one or more parameters, and processes the determined values with a battery performance model for online determination of the SOH and RUL.

Abstract: Performance and lifespan of batteries deteriorate with time due to various factors. Existing systems for battery management use different approaches for the battery management, and also rely on static value of parameters for State of Health (SOH) and Remaining Useful Life (RUL) estimation, thereby failing to consider current condition of the battery. The disclosure herein generally relates to battery management, and, more particularly, to a method and system for online battery management involving real-time estimation of State of Health (SOH) and Remaining Useful Life (RUL) of a battery, based on real-time data collected from the battery. The system determines state of the battery as one of charging, discharging, and rest. Further, corresponding to the determined state, the system determines values of one or more parameters, and processes the determined values with a battery performance model for online determination of the SOH and RUL.