Methods and systems are provided for driveline control and diagnostics. In one example, a vehicle system may include a controller with instructions stored in a first memory unit and when executed by a first processing unit cause the controller to write mechanical vehicle component operating data to a shared memory unit. The controller further includes instructions stored in a second memory unit that when executed by a second processing unit cause the controller to read the mechanical vehicle component operating data to determine data validity.

Embodiments described herein generally relate to the modification of State of Charge (SoC) calculations within electric vehicles (EVs). A database of data points may be generated based on characteristics of a battery cell at various measured SoCs within a controlled environment. Subsequently, during the operation of an EV, a battery management system (BMS) within the EV may collect various operating data points. The collected operating data points may be utilized to reference similar data points stored in the database in order to determine an SoC value. The SoC value may be utilized to modify or alter the SoC calculations by the BMS for an EV in operation.

Embodiments described herein generally relate to the modification of State of Charge (SoC) calculations within electric vehicles (EVs). A database of data points may be generated based on characteristics of a battery cell at various measured SoCs within a controlled environment. Subsequently, during the operation of an EV, a battery management system (BMS) within the EV may collect various operating data points. The collected operating data points may be utilized to reference similar data points stored in the database in order to determine an SoC value. The SoC value may be utilized to modify or alter the SoC calculations by the BMS for an EV in operation.

An apparatus for detecting a battery discharge cause for a vehicle includes a communicator connected to and configured to communicate with a plurality of controllers, and a monitor configured to monitor a communication state of the controllers to detect a battery discharge cause through the communicator. The monitor monitors the communication state of the controllers to check whether a controller in a communication-enabled state is present when the plurality of controllers is in a state of always-on power (power B+). The monitor checks whether the controller is maintained in the communication-enabled state until a preset amount of time elapses when a controller in a communication-enabled state is present. The monitor detects a communication non-sleep controller based on the controller maintained in the communication-enabled state until the preset amount of time elapses.

An apparatus for detecting a battery discharge cause for a vehicle includes a communicator connected to and configured to communicate with a plurality of controllers, and a monitor configured to monitor a communication state of the controllers to detect a battery discharge cause through the communicator. The monitor monitors the communication state of the controllers to check whether a controller in a communication-enabled state is present when the plurality of controllers is in a state of always-on power (power B+). The monitor checks whether the controller is maintained in the communication-enabled state until a preset amount of time elapses when a controller in a communication-enabled state is present. The monitor detects a communication non-sleep controller based on the controller maintained in the communication-enabled state until the preset amount of time elapses.

The present disclosure relates to systems, devices, and methods for analyzing health of vehicle batteries. Vehicle batteries tend to degrade over time. The described systems, devices, and methods quantify this degradation (or quantify remaining health of the battery) by comparing average energy used to charge or discharge the battery by a charge level unit to a nominal quantity of energy used to charge or discharge a battery in optimal health by a charge level unit. Charge data for previous charge events of the vehicle battery can be used in the calculation, and can be filtered by identifying qualified charge events based on at least one of a number of metrics. Usage data for previous usage events of the vehicle battery can be used in the calculation, and can be filtered by identifying qualified usage events or subgroups of usage event based on at least one of a number of metrics.

The present disclosure relates to systems, devices, and methods for analyzing health of vehicle batteries. Vehicle batteries tend to degrade over time. The described systems, devices, and methods quantify this degradation (or quantify remaining health of the battery) by comparing average energy used to charge or discharge the battery by a charge level unit to a nominal quantity of energy used to charge or discharge a battery in optimal health by a charge level unit. Charge data for previous charge events of the vehicle battery can be used in the calculation, and can be filtered by identifying qualified charge events based on at least one of a number of metrics. Usage data for previous usage events of the vehicle battery can be used in the calculation, and can be filtered by identifying qualified usage events or subgroups of usage event based on at least one of a number of metrics.

One embodiment of the present invention predicts a vehicular event relating to machinal performance using information obtained from interior and exterior sensors, vehicle onboard computer (“VOC”), and cloud data. The process of predication is able to activate interior and exterior sensors mounted on a vehicle operated by a driver for obtaining current data relating to external surroundings, interior settings, and internal mechanical conditions of the vehicle. After forwarding the current data to VOC to generate a current vehicle status representing real-time vehicle performance in accordance with the current data, retrieving a historical data associated with the vehicle including mechanical condition is retrieved. In one aspect, a normal condition signal is issued when the current vehicle status does not satisfy with the optimal condition based on the historical data. Alternatively, a race car condition is issued when the current vehicle status meets with the optimal condition.

One embodiment of the present invention predicts a vehicular event relating to machinal performance using information obtained from interior and exterior sensors, vehicle onboard computer (“VOC”), and cloud data. The process of predication is able to activate interior and exterior sensors mounted on a vehicle operated by a driver for obtaining current data relating to external surroundings, interior settings, and internal mechanical conditions of the vehicle. After forwarding the current data to VOC to generate a current vehicle status representing real-time vehicle performance in accordance with the current data, retrieving a historical data associated with the vehicle including mechanical condition is retrieved. In one aspect, a normal condition signal is issued when the current vehicle status does not satisfy with the optimal condition based on the historical data. Alternatively, a race car condition is issued when the current vehicle status meets with the optimal condition.

An indicator is provided in a vehicle for indicating necessity of change of a fuel vapor absorber in a venting line of a vehicle tank, especially a methanol tank for fuel cell vehicles.