Abstract: Various embodiments and approaches are described to minimize degradation of respective modules combined to form a battery pack onboard an electric vehicle (EV). Systems and components are presented to determine a respective operational state of the modules, and based thereon, a first subset of modules can be selected to provision power to various EV components while a second subset of modules can be deselected. Module selection can be based upon a threshold operating condition. A visual representation of the modules and their respective operational state can be presented, in conjunction with one or more alarms and recommended corrective operations. Artificial intelligence methods can be utilized to determine an operational state of a module(s). A module can be scheduled for replacement. Limiting degradation to a first module can minimize degradation of a second module. The various components can be stored in a memory and executed by a processor.

Abstract: Various embodiments and approaches are described to minimize degradation of respective modules combined to form a battery pack onboard an electric vehicle (EV). Systems and components are presented to determine a respective operational state of the modules, and based thereon, a first subset of modules can be selected to provision power to various EV components while a second subset of modules can be deselected. Module selection can be based upon a threshold operating condition. A visual representation of the modules and their respective operational state can be presented, in conjunction with one or more alarms and recommended corrective operations. Artificial intelligence methods can be utilized to determine an operational state of a module(s). A module can be scheduled for replacement. Limiting degradation to a first module can minimize degradation of a second module. The various components can be stored in a memory and executed by a processor.

Abstract: Various embodiments and approaches are described to minimize degradation of respective modules combined to form a battery pack onboard an electric vehicle (EV). Systems and components are presented to determine a respective operational state of the modules, and based thereon, a first subset of modules can be selected to provision power to various EV components while a second subset of modules can be deselected. Module selection can be based upon a threshold operating condition. A visual representation of the modules and their respective operational state can be presented, in conjunction with one or more alarms and recommended corrective operations. Artificial intelligence methods can be utilized to determine an operational state of a module(s). A module can be scheduled for replacement. Limiting degradation to a first module can minimize degradation of a second module. The various components can be stored in a memory and executed by a processor.

Abstract: Various embodiments and approaches are described to minimize degradation of respective modules combined to form a battery pack onboard an electric vehicle (EV). Systems and components are presented to determine a respective operational state of the modules, and based thereon, a first subset of modules can be selected to provision power to various EV components while a second subset of modules can be deselected. Module selection can be based upon a threshold operating condition. A visual representation of the modules and their respective operational state can be presented, in conjunction with one or more alarms and recommended corrective operations. Artificial intelligence methods can be utilized to determine an operational state of a module(s). A module can be scheduled for replacement. Limiting degradation to a first module can minimize degradation of a second module. The various components can be stored in a memory and executed by a processor.

Abstract: Various embodiments and approaches are described to minimize degradation of respective modules combined to form a battery pack onboard an electric vehicle (EV). Systems and components are presented to determine a respective operational state of the modules, and based thereon, a first subset of modules can be selected to provision power to various EV components while a second subset of modules can be deselected. Module selection can be based upon a threshold operating condition. A visual representation of the modules and their respective operational state can be presented, in conjunction with one or more alarms and recommended corrective operations. Artificial intelligence methods can be utilized to determine an operational state of a module(s). A module can be scheduled for replacement. Limiting degradation to a first module can minimize degradation of a second module. The various components can be stored in a memory and executed by a processor.

Abstract: Vehicle battery health optimization and communication (e.g., using a computerized tool) are enabled. For example, a system can comprise a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory, wherein the computer executable components comprise: a battery health component that, using a defined battery health algorithm and a battery sensor, determines degradation of a battery of a vehicle, and a communication component that, based on the degradation of the battery and a traveling direction of a user of the vehicle, external to the vehicle, transmits a message representative of the degradation of the battery.

Abstract: Various embodiments and approaches are described to minimize degradation of respective modules combined to form a battery pack onboard an electric vehicle (EV). Systems and components are presented to determine a respective operational state of the modules, and based thereon, a first subset of modules can be selected to provision power to various EV components while a second subset of modules can be deselected. Module selection can be based upon a threshold operating condition. A visual representation of the modules and their respective operational state can be presented, in conjunction with one or more alarms and recommended corrective operations. Artificial intelligence methods can be utilized to determine an operational state of a module(s). A module can be scheduled for replacement. Limiting degradation to a first module can minimize degradation of a second module. The various components can be stored in a memory and executed by a processor.

Abstract: Various embodiments and approaches are described to minimize degradation of respective modules combined to form a battery pack onboard an electric vehicle (EV). Systems and components are presented to determine a respective operational state of the modules, and based thereon, a first subset of modules can be selected to provision power to various EV components while a second subset of modules can be deselected. Module selection can be based upon a threshold operating condition. A visual representation of the modules and their respective operational state can be presented, in conjunction with one or more alarms and recommended corrective operations. Artificial intelligence methods can be utilized to determine an operational state of a module(s). A module can be scheduled for replacement. Limiting degradation to a first module can minimize degradation of a second module. The various components can be stored in a memory and executed by a processor.

Abstract: Automated vehicle battery health optimization (e.g., using a computerized tool) is enabled. For example, a system can comprise a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory, wherein the computer executable components comprise: a battery health component that, using a defined battery health algorithm and a battery sensor, determines degradation of a battery of a vehicle, and an execution component that, based on the degradation of the battery and a traveling direction of a user of the vehicle, external to the vehicle, facilitates an action determined to mitigate further degradation of the battery.

Abstract: A battery module with removable cells and a battery management system or charging station system that determines the number of cells to use for a given trip. Thus, the system receives trip information (starting point, destination, stops, etc.) and determines the number of cells required for the trip, optionally based on traffic conditions, weather, prior driving habits, cell state of charge (SOC), cell state of health (SOH), and the like. The system can recommend which cells to leave in the vehicle, which cells to remove from the vehicle, which cells to place in the vehicle, which cells to charge, and the like, via a visual indicator. Importantly, a number of cells actually required for the trip can be suggested, without extra cells, such that extra weight in terms of unused cells may be removed from the vehicle, thereby increasing trip efficiency.

Abstract: A battery charging system with enhanced time-based charging and coupling detection, as well as battery health monitoring. A user provides a time available for charging to the vehicle, a mobile device, or a charging station directly. In the case that the time available for charging is provided to the vehicle or the mobile device, this information, as well as battery health information, is then shared with the charging station when the charging station detects coupling of the associated connector/coupler to the vehicle, or when the vehicle is detected within a predetermined proximity of the charging station. When the vehicle is connected to the charging station and charging commences, a standard charging power may be utilized or a charging power may be selected and utilized such that enhanced or optimized charging can be provided for the available time period.

Abstract: A battery charging system with enhanced time-based charging and coupling detection, as well as battery health monitoring and battery cell selection. A user provides a time available for charging to the vehicle or a mobile device and indirectly to a charging station, or the charging station directly. The time available for charging, as well as battery health information, is shared with the charging station when the charging station detects coupling of the associated connector/coupler to the vehicle, or when the vehicle is detected within a predetermined proximity of the charging station. Subsequently, a standard charging power may be utilized or a charging power may be selected and utilized such that enhanced or optimized charging can be provided for the available time period. A battery control unit identifies degraded or faulted battery cells and charging of these battery cells is avoided or deprioritized.

Abstract: A battery system that, based upon the state of charge (SOC), state of health (SOH), and discharge profile of a battery module, or removable cells of the battery module, apprises the user of optimal or allowable storage temperature and time before the charge and range of a fully charged battery module or removable cell is degraded. In the event that this optimal or allowable storage temperature or time is deviated from or exceeded, the battery system recalculates the necessary charging power and time to meet the original range calculation and satisfy original trip requirements. This may be utilized for cells stored both in the vehicle and cells stored remote from the vehicle.

Abstract: A battery system that collects and considers multiple variables to provide optimal charge and range information, either on a battery module or per cell basis. This system may provide the required charge time to complete a trip and provides a minimum SOC, which may be achieved by charging or via cell swapping. Variables considered may include expected traffic conditions for a trip, expected temperature for a trip, expected wind conditions for the trip, expected trip topography, etc., all gathered prior to the start of and/or updated during the trip. Based on this smart range estimation, the system can provide the cell swaps required, the number cells to charge, the expected charging time required, and alert the user if charge/swap related stops will be required during the trip in order to successfully complete the trip.

Abstract: A battery charging system with enhanced time-based charging and coupling detection. A user provides a time available for charging to a control unit of the vehicle, a mobile device of the user, or a control unit of a charging station directly. In the case that the time available for charging is provided to the control unit of the vehicle or the mobile device of the user, this information is then shared with the control unit of the charging station when the control unit of the charging station detects coupling of the associated connector/coupler to the vehicle, or when the vehicle is detected within a predetermined proximity of the charging station. When the vehicle is connected to the charging station and charging commences, a standard charging power may be utilized or a charging power may be selected and utilized such that enhanced charging can be provided in the available time period.

Abstract: A battery charging system with enhanced time-based charging, which may be static or dynamic. A user provides a time available for charging a vehicle to a control unit of the vehicle, a mobile device of the user, or a control unit of a charging station directly. In any case, this information is received by the control unit of the charging station via a wired connection, a wireless connection, a near field connection, a cloud network, or directly. When the vehicle is connected to the charging station and charging commences, a charging power is selected and utilized such that enhanced charging can be provided in the available time period, illustratively providing as much charge as possible in the available time period. This charging power may be modified responsive to user changes to the available charging time while charging is ongoing.

Abstract: A battery charging system with enhanced time-based charging and coupling detection, as well as battery health monitoring. A user provides a time available for charging to the vehicle, a mobile device, or a charging station directly. In the case that the time available for charging is provided to the vehicle or the mobile device, this information, as well as battery health information, is then shared with the charging station when the charging station detects coupling of the associated connector/coupler to the vehicle, or when the vehicle is detected within a predetermined proximity of the charging station. When the vehicle is connected to the charging station and charging commences, a standard charging power may be utilized or a charging power may be selected and utilized such that enhanced or optimized charging can be provided for the available time period.

Abstract: An anonymization apparatus 6 is proposed for the generation of anonymized images 9, wherein surveillance images 5 are provided through video surveillance of a surveillance region 3 by means of at least one camera 2, with a recognition module 11, wherein the surveillance images 5 are provided to the recognition module 11, wherein the recognition module 11 is configured to recognize persons 4 contained in the surveillance images 5, with a processing module 13, wherein the processing module 13 is configured to process the surveillance images 5 into the anonymized images 9, wherein at least one person 4 or person segment included in the surveillance images 5 is anonymized in the anonymized images 9, wherein the processing module 13 is configured to replace the recognized person 4 or person segment by an animated person model 14 for the purpose of anonymization.

Abstract: An anonymization apparatus 6 is proposed for the generation of anonymized images 9, wherein surveillance images 5 are provided through video surveillance of a surveillance region 3 by means of at least one camera 2, with a recognition module 11, wherein the surveillance images 5 are provided to the recognition module 11, wherein the recognition module 11 is configured to recognize persons 4 contained in the surveillance images 5, with a processing module 13, wherein the processing module 13 is configured to process the surveillance images 5 into the anonymized images 9, wherein at least one person 4 or person segment included in the surveillance images 5 is anonymized in the anonymized images 9, wherein the processing module 13 is configured to replace the recognized person 4 or person segment by an animated person model 14 for the purpose of anonymization.

Abstract: A method for determining a viewing direction of a person, such as a driver in a motor vehicle, is provided. The method includes detecting a surface contour of a surface of an eye of the person, ascertaining a normal vector on the surface of the eye depending on the detected surface contour, and determining the viewing direction of the person depending on the normal vector.