Abstract: A system and method for ordering and scheduling food orders. The system considers hard and soft requirements for one or more customers, a restaurant's capacity to serve assigned meals, and restaurant variety. The system and method may automatically select menu items from assigned restaurants based on food requirements and amount of food required.

Abstract: System and methods for estimating a relationship between a SOC and an OCV of a battery system included in a vehicle are presented. In certain embodiments, an initial relationship between an open circuit voltage (“OCV”) and a state of charge (“SOC”) of a cell of the battery system may be determined at a beginning of life of the cell. Changes in one or more stoichiometric points of a half-cell of the cell may be determined as the cell ages. Based on the determined stoichiometric point changes of the half-cell, an initial relationship between the OCV and the SOC of the cell may be adjusted to generate an updated relationship between the OCV and the SOC of the cell.

Abstract: A number of variations include a method, which may include using at least a segment of voltage-based Battery State Estimation data, and using real-time linear regression, which may be a method of estimating future behavior of a system based on current and previous data points, to provide a robust and fast-adapting impedance response approximator. Linear regression may be performed by forming an RC circuit which is “equivalent” to electrochemical impedance spectroscopy data and processing the runtime values of that RC circuit using any number of known real-time linear regression algorithms including, but not limited, to a weighted recursive least squares (WRLS), Kalman filter or other means.

Abstract: System and methods for estimating a future power capability of a battery system included in a vehicle are presented. In some embodiments, a method for estimating a future power capability of a battery system may include determining an initial battery voltage when the battery operates at a current limit and estimating a future battery current at a first time when the battery operates at the associated voltage limit based on the initial battery current. A future battery voltage at the first time when the battery operates at the associated current limit may be determined based on the initial battery voltage. An estimated voltage-limited power capability of the battery at the first time may be determined based on the future battery current and an estimated current-limited power capability of the battery at the first time may be determined based on the future battery voltage.

Abstract: System and methods for estimating a capacity of a battery system and/or a constituent cell and/or pack included in a vehicle are presented. In certain embodiments, a method for estimating a capacity of a battery system may include determining voltage-based state of charge (“SOC”) data of a pack of the battery system based on measured pack voltage information and a relationship between an open circuit voltage (“OCV”) and the SOC of the pack of at a beginning of life of the pack. Beginning of life SOC data of the pack may be determined based on coulomb counting measurements, and a ratio may be determined based on the beginning of life SOC data of the pack and the voltage-based SOC data of the pack. An estimated present capacity of the pack may be determined based on the beginning of life capacity of the pack and the ratio.

Abstract: A fuel cell system that determines the phase transition from water to gas through a bleed/drain valve in a water separation device. The fuel cell system includes a fuel cell stack having an anode side and a cathode side. An injector injects hydrogen gas into the anode side of the fuel cell stack. The water separation device receives an anode exhaust gas from the anode side of the fuel cell stack, where the water separation device includes a water holding reservoir. A controller controls the injector and the bleed/drain valve and determines when the bleed/drain valve transitions from draining water to bleeding the anode exhaust gas by comparing the flow rate through the water separation device and the flow rate through the injector.

Abstract: System and methods for estimating a capacity of a battery are presented. A measure of data skewness may be calculated from a battery system terminal voltage measurement. Inflection points in the data skewness of the terminal voltage measurement may align with transition points associated with a battery system. These transitions points may be associated with known SOCs determined from testing and/or characterization of the battery system. Using the detected transitions and associated SOCs and an indication of an accumulated charge provided to/from the battery between the transitions, an estimated capacity of the battery system may be determined.

Abstract: Adaptive estimation techniques to create a battery state estimator to estimate power capabilities of the battery pack in a vehicle. The estimator adaptively updates circuit model parameters used to calculate the voltage states of the ECM of a battery pack. The adaptive estimation techniques may also be used to calculate a solid-state diffusion voltage effects within the battery pack. The adaptive estimator is used to increase robustness of the calculation to sensor noise, modeling error, and battery pack degradation.

Abstract: System and methods for estimating a capacity of a battery are presented. In certain embodiments, charge and discharge current throughput data may be separately accumulated during operation of a battery system (e.g., during a charge sustaining operation of vehicle associated with the battery system). Charge and discharge voltage-based state of charge movement data may be further separately accumulated. Upon accumulating sufficient data, estimated charge and discharge battery capacities may be determined based on the accumulated data.

Abstract: System and methods for estimating a capacity of a battery system and/or a constituent cell and/or pack included in a vehicle are presented. In certain embodiments, a method for estimating a capacity of a battery system may include determining voltage-based state of charge (“SOC”) data of a pack of the battery system based on measured pack voltage information and a relationship between an open circuit voltage (“OCV”) and the SOC of the pack of at a beginning of life of the pack. Beginning of life SOC data of the pack may be determined based on coulomb counting measurements, and a ratio may be determined based on the beginning of life SOC data of the pack and the voltage-based SOC data of the pack. An estimated present capacity of the pack may be determined based on the beginning of life capacity of the pack and the ratio.

Abstract: System and methods for estimating a future power capability of a battery system included in a vehicle are presented. In some embodiments, a method for estimating a future power capability of a battery system may include determining an initial battery voltage when the battery operates at a current limit and estimating a future battery current at a first time when the battery operates at the associated voltage limit based on the initial battery current. A future battery voltage at the first time when the battery operates at the associated current limit may be determined based on the initial battery voltage. An estimated voltage-limited power capability of the battery at the first time may be determined based on the future battery current and an estimated current-limited power capability of the battery at the first time may be determined based on the future battery voltage.

Abstract: System and methods for estimating a relationship between a SOC and an OCV of a battery system included in a vehicle are presented. In certain embodiments, an initial relationship between an open circuit voltage (“OCV”) and a state of charge (“SOC”) of a cell of the battery system may be determined at a beginning of life of the cell. Changes in one or more stoichiometric points of a half-cell of the cell may be determined as the cell ages. Based on the determined stoichiometric point changes of the half-cell, an initial relationship between the OCV and the SOC of the cell may be adjusted to generate an updated relationship between the OCV and the SOC of the cell.

Abstract: System and methods for determining battery system power capability in a vehicle are presented. Peak power capability estimation systems and methods disclosed herein may compensate regressed parameters in a battery system circuit model for an effect of current magnitude. Utilizing the disclosed methods for accurately estimating peak power capability of a battery system may provide for, among other things, improved battery system performance modeling and/or improved battery system control and management decisions.

Abstract: A battery state estimator which combines an electrochemical solid-state concentration model with an empirical equivalent-circuit model. The battery state estimator uses a reduced-order physics-based electrochemical solid-state concentration model to calculate open circuit voltage of a battery cell, and uses the calculated open circuit voltage in an equivalent-circuit model to evaluate a diffusion voltage drop and other battery cell parameters. The battery state estimator is implemented in an online estimator framework using an extended Kalman filter, with a measured terminal voltage and measured current as inputs. A state of charge of the battery cell can be determined from the calculated open circuit voltage, and the state of charge along with the other parameters from the equivalent-circuit model are used to evaluate battery pack performance and to control battery pack charging and discharging.

Abstract: A number of illustrative variations may include a method, which may include using at least a segment of impedance-based battery power capability estimation data, and using real-time linear regression, which may be used as a method of estimating future behavior of a system based on current and previous data points, to provide a robust state of power predictor.

Abstract: Systems and methods for improvements in battery state of charge accuracy, charge termination consistency, capacity estimation, and energy delivery consistency. More specifically, embodiments herein detail systems and methods using an algorithm to calculate the change in state of charge for a given voltage change (dSOC/dV) at a given temperature in a region around the present voltage measurement or estimation and to set a signal indicating when the measurement should not be used due to potential error.

Abstract: System and methods for estimating a capacity of a battery are presented. In certain embodiments, charge and discharge current throughput data may be separately accumulated during operation of a battery system (e.g., during a charge sustaining operation of vehicle associated with the battery system). Charge and discharge voltage-based state of charge movement data may be further separately accumulated. Upon accumulating sufficient data, estimated charge and discharge battery capacities may be determined based on the accumulated data.

Abstract: System and methods for determining battery system power capability in a vehicle are presented. Peak power capability estimation systems and methods disclosed herein may compensate regressed parameters in a battery system circuit model for an effect of current magnitude. Utilizing the disclosed methods for accurately estimating peak power capability of a battery system may provide for, among other things, improved battery system performance modeling and/or improved battery system control and management decisions.

Abstract: A number of variations include a method, which may include using at least a segment of voltage-based Battery State Estimation data, and using real-time linear regression, which may be a method of estimating future behavior of a system based on current and previous data points, to provide a robust and fast-adapting impedance response approximator. Linear regression may be performed by forming an RC circuit which is “equivalent” to electrochemical impedance spectroscopy data and processing the runtime values of that RC circuit using any number of known real-time linear regression algorithms including, but not limited, to a weighted recursive least squares (WRLS), Kalman filter or other means.