Abstract: This application relates to apparatus and methods for generating, and executing, surrogate models. In some examples, a computing device generates and evaluates correlations between input and output variables for a system to identify highly correlated input and output parameters. In addition, weights for one or more of the parameters may be determined. The computing device identifies a mathematical relationship between input and output variables to generate a physics model. The computing device may also identify other features not captured by the physical relationship that are highly correlated to each other, and generates a feature model that is based on the highly correlated features. The computing device may optimize the feature model based on a culling process that reduces the computational resources required to execute the feature model. The physics model is then combined with the feature model to generate a system output model that can simulate the system.

Abstract: This application relates to apparatus and methods for generating, and executing, surrogate models. In some examples, a computing device generates and evaluates correlations between input and output variables for a system to identify highly correlated input and output parameters. In addition, weights for one or more of the parameters may be determined. The computing device identifies a mathematical relationship between input and output variables to generate a physics model. The computing device may also identify other features not captured by the physical relationship that are highly correlated to each other, and generates a feature model that is based on the highly correlated features. The computing device may optimize the feature model based on a culling process that reduces the computational resources required to execute the feature model. The physics model is then combined with the feature model to generate a system output model that can simulate the system.

Abstract: This application relates to apparatus and methods for determining the integrity of data, such as sensor data, in systems. In some examples, a computing device receives input data for the system, and executes a physics-based model to generate a first output. The physics-based model may include a plurality of surrogate models that simulate various portions of the system. The computing device may further execute a machine learning model that operates on the first output to generate a second output. The computing device may generate a predicted output for the system based on the first output and the second output. In some examples, the computing device determines an error for the system based on the predicted output and sensor data received from sensors for the system. Based on the error, the computing device determines if the sensor data is valid. The computing device may then provide an indication of the determination.

Abstract: This application relates to apparatus and methods for electronically generating, and executing, component models for systems and system components, and determining component options for the system based on the executed component models. In some examples, a computing device generates component models for one or more components of a system. The component models may be based on features, inputs, and outputs to each system component. The computing device may execute the component models to determine one or more requirements for each component. The computing device may then search a database to determine component options that can satisfy the one or more requirements. In some examples, the computing device may display the determined component options, and may allow for the selection of one or more of the determined component options. In some examples, the computing device may allow for the purchase of the component options.

Abstract: This application relates to apparatus and methods for generating, and executing, surrogate models. In some examples, a computing device generates and evaluates correlations between input and output variables for a system to identify highly correlated input and output parameters. In addition, weights for one or more of the parameters may be determined. The computing device identifies a mathematical relationship between input and output variables to generate a physics model. The computing device may also identify other features not captured by the physical relationship that are highly correlated to each other, and generates a feature model that is based on the highly correlated features. The computing device may optimize the feature model based on a culling process that reduces the computational resources required to execute the feature model. The physics model is then combined with the feature model to generate a system output model that can simulate the system.

Abstract: A method of forming hydrogen gas comprises the steps of providing a reactor and providing a hydrogen-generating composition to the reactor. The hydrogen-generating composition consists essentially of a borohydride component and a glycerol component. The borohydride, e.g. sodium borohydride, and glycerol components are present in a generally three (3) to four (4) stoichiometric ratio, prior to reaction. The borohydride component has hydrogen atoms and the glycerol component has hydroxyl groups with hydrogen atoms. The method further comprises the step of reacting the borohydride component with the glycerol component thereby converting substantially all of the hydrogen atoms present in the borohydride component and substantially all of the hydrogen atoms present in the hydroxyl groups of the glycerol component to form the hydrogen gas. The reaction between the borohydride component and the glycerol component is an alcoholysis reaction.

Abstract: The disclosure relates to an integrated energy management system for managing thermal and electrical energy in a fuel cell coupled refrigeration system. In one example, a refrigeration cycle is driven by heat provided alternatively by a fuel cell and an electric heating device. In another example, a refrigeration cycle is driven by heat provided by a fuel cell to reduce consumption of electrical grid supplied power.

Abstract: Disclosed are fuel cell coupled refrigeration systems and to the use of fuel cells to provide thermal energy to a refrigeration system. More particularly, a heat exchanger couples, directly or indirectly, to a fuel cell and a heat driven refrigeration system to transfer at least a portion of thermal energy generated by the fuel cell to the refrigeration system, thereby driving a refrigeration cycle of the refrigeration system.

Abstract: A vehicle power plant includes a high temperature PEM fuel cell system operatively connected to a battery pack. A power conditioner is operatively connected between the PEM fuel cell system and the battery pack. The system can include a fuel processor, such as a steam reformer or an autothermal reformer. The reformer can be designed such that it can reform a wide range of fuels. The system can provide for a vehicle with a much higher driving range at a potentially lower cost than an equivalent range battery-only electric vehicle. The integration of these components into a single system also allows the vehicle to be fuel flexible; that is, capable of being fueled with a wide range of fuels without hardware changes in the system.

Abstract: A method of forming hydrogen gas comprises the steps of providing a reactor and providing a hydrogen-generating composition to the reactor. The hydrogen-generating composition consists essentially of a borohydride component and a glycerol component. The borohydride, e.g. sodium borohydride, and glycerol components are present in a generally three (3) to four (4) stoichiometric ratio, prior to reaction. The borohydride component has hydrogen atoms and the glycerol component has hydroxyl groups with hydrogen atoms. The method further comprises the step of reacting the borohydride component with the glycerol component thereby converting substantially all of the hydrogen atoms present in the borohydride component and substantially all of the hydrogen atoms present in the hydroxyl groups of the glycerol component to form the hydrogen gas. The reaction between the borohydride component and the glycerol component is an alcoholysis reaction.