ENERGY MANAGEMENT METHOD FOR AN ELECTRIC VEHICLE

• US 20140350763A1
• Filed: 12/07/2012
• Published: 11/27/2014
• Est. Priority Date: 12/14/2011
• Status: Active Grant

• Current Assignee: Renault Sas (Renault)
• Original Assignee: Renault Sas (Renault)
• Inventors: Granato, Giovanni, Aouchiche, Kamal, Bonnans, Joseph Frederic, Zidani, Hasnaa, Rousseau, Gregory
• Granted Patent: US 10,029,667 B2
• Time in Patent Office: Days
• US Class Current: 701/22
• CPC Class Codes: B60K 6/20 the prime-movers consisting of electric motors and internal combustion engines, e.g. HEVs
• CPC Class Codes: B60W 10/06 including control of combustion engines
• CPC Class Codes: B60W 10/08 including control of electric propulsion units, e.g. motors or generators
• CPC Class Codes: B60W 20/00 Control systems specially adapted for hybrid vehicles hybrid vehicle design, B60K6/00; electric vehicles B60L
• CPC Class Codes: B60W 2552/05 Type of road, e.g. motorways, local streets, paved or unpaved roads
• CPC Class Codes: B60W 2552/10 Number of lanes
• CPC Class Codes: B60W 2552/15 Road slope, i.e. the inclination of a road segment in the longitudinal direction
• CPC Class Codes: B60W 2552/20 Road profile, i.e. the change in elevation or curvature of a plurality of continuous road segments
• CPC Class Codes: B60W 2552/30 Road curve radius
• CPC Class Codes: B60W 2554/00 Input parameters relating to objects
• CPC Class Codes: B60W 2554/4042 Longitudinal speed
• CPC Class Codes: B60W 2555/60 Traffic rules, e.g. speed limits or right of way
• CPC Class Codes: B60W 2556/10 Historical data
• CPC Class Codes: B60W 2556/50 of positioning data, e.g. GPS [Global Positioning System] data
• CPC Class Codes: B60W 30/1882 characterised by the working point of the engine, e.g. by using engine output chart
• CPC Class Codes: B60W 50/0097 Predicting future conditions
• CPC Class Codes: Y02T 10/40 Engine management systems
• CPC Class Codes: Y02T 10/62 Hybrid vehicles
• CPC Class Codes: Y02T 10/84 Data processing systems or methods, management, administration

Abstract

A method managing energy consumption for an automobile including an electric battery and a heat engine, to select use phases of the engine along a route to minimize fuel consumption. The method includes: cutting a road network, for a route, into plural segments each defined by an input node and an output node; calculating, from a speed associated with a segment, a probability of a speed transition between a speed at an input node and at an output node of the segment, considering plural speeds at the input node and at the output node, executed gradually over all the route segments; applying a stochastic optimization algorithm considering all possible transition scenarios between each input node and each output node, and the probability associated therewith, and a fuel consumption model between two successive nodes, executed over all the route segments; and selecting use phases of the heat engine along the route.

Claims

1-8. -8. (canceled)

9. A method for managing energy consumption for an automotive vehicle including an electric battery and an engine, the method making it possible to select phases of use of the engine along a given route, to minimize fuel consumption of the vehicle, the method comprising:

cutting a road network taken into consideration for a given route into plural segments, each segment being delimited by an entry node and an exit node;

computing a probability of a speed transition between a speed at an entry node and a speed at an exit node of a segment, based on a speed associated with the segment, and by considering plural speeds at the entry node and plural speeds at the exit node, the computing carried out gradually on all the segments of the route;

applying a stochastic optimization algorithm taking into account possible scenarios of transition between each entry node and each exit node along the route, and their associated probability, and a model of fuel consumption between two successive nodes, and which is dependent on a speed of the vehicle between the nodes and on a state of charge of the battery; and

selecting phases of use of the engine along the route.

10. The method as claimed in claim 9, wherein the estimating the transition probabilities is performed based on a travel history of the vehicle along the route considered, and based on speeds recorded along the route.

11. The method as claimed in claim 9, wherein the method proceeds gradually for each segment of the route, and begins from a last segment and tracks progressively toward a first segment of the route.

12. The method as claimed in claim 9, wherein the method can be recommenced at each node of the route, to take account of an actual state of charge of the battery at the node considered.

13. The method as claimed in claim 9, wherein the cutting the route into segments is carried out automatically by a standard navigator.

14. The method as claimed in claim 9, wherein the cutting the route into segments is carried out manually.

15. The method as claimed in claim 9, wherein a determination of transition probabilities during the computing can be refined by taking into account at least one parameter to be chosen from among a time of day, a state of automobile traffic, a type of road, or a number of lanes.

16. The method as claimed in claim 9, taking into consideration following events:

the engine must be stopped when the engine does not yield any power;

it is necessary to comply with a time interval of a few minutes between each stoppage and each switch-on of the engine;

between a moment at which the engine is switched on and a moment at which the engine is active and yields power, there exists a latency time of a few minutes.