An electronic control unit of a vehicle having an automatic park-range switching function for automatically turning off a power supply after switching to a P range when a power-off operation is performed, wherein when a power-off operation is performed in a state where the automatic park-range switching function is disabled by a predetermined special operation, the vehicle is turned off in a state where the vehicle is in a neutral range and the power supply is turned off in a state where power supply to the electrical components is interrupted. As a result, the vehicle is parked in a movable state, and battery exhaustion of the power supply is suppressed.

An electronic control unit of a vehicle having an automatic park-range switching function for automatically turning off a power supply after switching to a P range when a power-off operation is performed, wherein when a power-off operation is performed in a state where the automatic park-range switching function is disabled by a predetermined special operation, the vehicle is turned off in a state where the vehicle is in a neutral range and the power supply is turned off in a state where power supply to the electrical components is interrupted. As a result, the vehicle is parked in a movable state, and battery exhaustion of the power supply is suppressed.

According to one aspect, an autonomous vehicle includes hardware systems which receive relatively low voltage from a low voltage power distribution unit (LVPDU). An LVPDU includes a power source such as a DC-DC converter and a plurality of backup batteries. The plurality of backup batteries is configured to provide backup power to subsets of components arranged to effectively all be powered by the power source onboard the LVPDU. The backup batteries may be tested, substantially while LVPDU is being used to provide power. The backup batteries may be charged substantially in parallel.

A control system controls power supply in a vehicle. The control system includes sub-power managers and an integrated power manager. The sub-power managers control respective output power of a plurality of subsystems that actualize functions of the vehicle. The integrated power manager performs integrated control of output power in the overall vehicle by exchanging information with the plurality of sub-power managers. The information that is exchanged between the plurality of sub-power managers and the integrated power manager includes information that enables calculation of a physical quantity that is expressed by at least either of a power dimension and an energy dimension.

A vehicle control device includes: a first control unit configured to charge a power storage element of a secondary power supply to a predetermined value; a second control unit configured to, when the power storage element is charged to the predetermined value, execute an automated parking function by outputting first electric power at a specified voltage from a primary power supply to an automated parking system while continuing to charge the power storage element; a third control unit configured to detect a sign of failure of the primary power supply during execution of the automated parking function; and a fourth control unit configured to, when the sign of failure of the primary power supply is detected, output second electric power at a voltage lower than the specified voltage from the secondary power supply to the automated parking system in parallel with the first electric power.

Systems and methods related to distributed subsystems with embedded artificial intelligence (AI) compute in automotive systems are disclosed herein. A disclosed automotive computing architecture includes a network, a plurality of networked subsystems in operative communication using the network, and a set of AI accelerators in a one-to-one correspondence with the plurality of networked subsystems. The set of AI accelerators may conduct AI computations for their respective networked subsystems without using the network, reducing latency. The set of distributed AI accelerators may each be optimized for the specific workloads of their subsystems. By using distributed AI accelerators, each task can be handled by hardware optimized for its specific needs, resulting in higher efficiency, lower latency, and better power management. Furthermore, the distributed AI accelerators can provide greater scalability, redundancy, and fault tolerance, enabling better performance across diverse workloads.