Abstract: In one aspect, based on at least a received first state of health of a battery pack and an initial state of charge of the battery pack, a method may include determining, by a state of charge estimator of a digital twin battery model, states of charges for the battery pack. Based on the states of charges for the battery pack, the method may include determining, by a voltage predictor of the digital twin battery model, predicted battery voltages. Based on the predicted battery voltages, the method may include determining, by a state of charge corrector of the digital twin battery model, a voltage difference between the predicted battery voltages and measured voltages. Based on the voltage difference, the method may include correcting, by the state of charge corrector, the states of charges to generate corrected states of charges for the battery pack.

Abstract: In one aspect, a method may include generating an aging battery dataset including information pertaining to age histories of electric vehicles, cell manufacturer specifications, and laboratory tests. Based on the information and battery health metrics associated with battery pack modules, the method may include predicting a first state of health of the battery pack modules. The method may include receiving a second state of health of the battery pack modules, wherein the second state of health is determined based on determined states of charges for the battery pack modules. The method may include determining an uncertainty for the second state of health using a rest duration after and before charging of the battery pack modules. Based on the uncertainty, the first state of health, and the second state of health, the method may include determining a confidence score for the second state of health of the battery pack modules.

Abstract: In one aspect, a computer-implemented method may include receiving charge cycle data pertaining to a battery pack. The method may include determining, based on the charge cycle data, whether a noise level of a battery management system exceeds a first threshold. In response to determining the noise level exceeds the first threshold, the method may include determining an initial state of charge of the battery pack using coulomb counting by reversing the charge cycle data. In response to determining the noise level does not exceed the first threshold, the method may include determining whether a rest time before charge cycle exceeds a second threshold. In response to determining the rest time before charge cycle does not exceed the second threshold, the method may include determining the initial state of charge of the battery pack using coulomb counting by reversing the charge cycle data.

Abstract: The present invention describes a mannoprotein solution which has a turbidity, when measured by nephelometry at a concentration of 200 g/l of mannoprotein and at a pH in the range of pH 4 to pH 8 lower than 70 NTU, preferably lower than 60 NTU, more preferably lower than 50 NTU, most preferably lower than 40 NTU. This solution can be advantageously used in the stabilisation of wine against tartrate salt precipitation because it is very clear and can be added directly to the wine without causing any turbidity.

Abstract: The present invention describes a process to improve the activity as wine stabiliser of a mannoprotein, comprising treating a mannoprotein with a basic solution at a pH of at least 9. The mannoprotein obtainable by this process is more effective in stabilising wine against tartrate precipitation or protein haze formation when compared with the mannoprotein prior to the treatment with basic solution.