US 12,442,650 B2
Navigation map learning for intelligent hybrid-electric vehicle planning
Kyle Hollins Wray, Fremont, CA (US); David Ilstrup, Santa Cruz, CA (US); Liam Pedersen, San Francisco, CA (US); Richard Lui, Sunnyvale, CA (US); and Christopher Ostafew, Mountain View, CA (US)
Assigned to Nissan North America, Inc., Franklin, TN (US)
Filed by Nissan North America, Inc., Franklin, TN (US)
Filed on Jan. 16, 2024, as Appl. No. 18/413,855.
Application 18/413,855 is a continuation of application No. 17/130,490, filed on Dec. 22, 2020, granted, now 11,946,760.
Prior Publication US 2024/0159551 A1, May 16, 2024
Int. Cl. G01C 21/34 (2006.01); B60W 10/06 (2006.01); B60W 10/08 (2006.01); B60W 20/14 (2016.01); B60W 30/18 (2012.01); B60W 40/08 (2012.01); G01C 21/00 (2006.01); G01S 19/42 (2010.01)
CPC G01C 21/3469 (2013.01) [B60W 10/06 (2013.01); B60W 20/14 (2016.01); B60W 40/08 (2013.01); G01C 21/3807 (2020.08); G01S 19/42 (2013.01); B60W 10/08 (2013.01); B60W 30/18127 (2013.01); B60W 2510/244 (2013.01); B60W 2520/105 (2013.01); B60W 2540/10 (2013.01); B60W 2540/12 (2013.01); B60W 2552/15 (2020.02); B60W 2555/20 (2020.02)] 20 Claims
OG exemplary drawing
 
1. A method for engine activation planning in a hybrid electric vehicle (HEV), the method comprising:
analyzing historical driving data of the HEV to identify recurring driving patterns of behavior specific to a driver of the HEV;
recording data related to one or more vehicle parameters as the HEV drives along a road segment of a predetermined length;
predicting future driving patterns of behavior as to where the driver is likely to go based on the historical driving data;
generating an engine activation policy for the HEV to control total energy consumption, wherein the engine activation policy optimizes charging of a battery and usage of the battery in response to the future driving patterns and the data recorded;
measuring wasted energy as the HEV drives along the road segment, wherein the wasted energy is energy that cannot be stored in the battery;
analyzing the total energy consumption, the wasted energy, and the usage of the battery of the engine activation policy based upon selected objectives;
weighting the total energy consumption, the wasted energy, and the usage of the battery of the engine activation policy based upon the analyzing of the engine activation policy to update the engine activation policy for the HEV based upon the selected objectives to create a weighted engine activation policy; and
using the weighted engine activation policy to control activation of a gasoline engine in the HEV, wherein a control decision is continuously adjusted, in real time, based on the weighted engine activation policy and real time driving conditions.