Energy prediction device
AssigneeDenso Corporation
InventorsYuki Kishita, Hiroyuki Nanjo, Noriaki Ikemoto
Life of this patent
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Abstract
An energy prediction device includes a route setting unit configured to divide a travel route traveled by a vehicle and set route sections into which the travel route is divided and a model construction unit configured to construct a consumption prediction model for predicting an energy consumed by the vehicle for each route section.
Claims11
An energy prediction device comprising:
- a route setting unit configured to divide a travel route traveled by a vehicle and sets route sections into which the travel route is divided;
- and
- a model construction unit configured to construct a consumption prediction model for predicting an energy consumed by the vehicle for each route section, and
- an information acquisition unit configured to acquire condition information about the energy consumed when the vehicle travels the travel route, wherein
- the route setting unit is configured to divide the travel route and set route sections into which the travel route is divided, based on proximity of the condition information.
An energy prediction device comprising:
- a route setting unit configured to divide a travel route traveled by a vehicle and sets route sections into which the travel route is divided;
- and
- a model construction unit configured to construct a consumption prediction model for predicting an energy consumed by the vehicle for each route section,
- the model construction unit is configured to construct the consumption prediction model as a learning model with explanatory variables and an objective variable,
- the explanatory variables include at least one of weather information, a road condition, time information, and driver information, and
- the objective variable includes at least one of a metric for each vehicle speed pattern and a metric for energy consumed.
An energy prediction method comprising:
- dividing a travel route traveled by a vehicle and sets route sections into which the travel route is divided;
- and
- constructing a consumption prediction model for predicting an energy consumed by the vehicle for each route section, and
- acquiring condition information about the energy consumed when the vehicle travels the travel route, wherein
- the travel route is divided and the route sections are set based on the proximity of condition information.
A non-transitory computer readable medium having stored thereon instructions executable by a computer to cause the computer to perform an energy prediction method, comprising:
- dividing a travel route traveled by a vehicle and sets route sections into which the travel route is divided;
- and
- constructing a consumption prediction model for predicting an energy consumed by the vehicle for each route section, and
- acquiring condition information about the energy consumed when the vehicle travels the travel route, wherein
- the travel route is divided and the route sections are set based on the proximity of condition information.
An energy prediction method comprising:
- dividing a travel route traveled by a vehicle and sets route sections into which the travel route is divided;
- and
- constructing a consumption prediction model for predicting an energy consumed by the vehicle for each route section, wherein
- the consumption prediction model is constructed as a learning model with explanatory variables and an objective variable,
- the explanatory variables include at least one of weather information, a road condition, time information, and driver information, and
- the objective variable includes at least one of a metric for each vehicle speed pattern and a metric for energy consumed.
A non-transitory computer readable storage medium having stored thereon instructions executable by a computer to cause the computer to perform an energy prediction method, comprising:
- dividing a travel route traveled by a vehicle and sets route sections into which the travel route is divided;
- and
- constructing a consumption prediction model for predicting an energy consumed by the vehicle for each route section, wherein
- the consumption prediction model is constructed as a learning model with explanatory variables and an objective variable,
- the explanatory variables include at least one of weather information, a road condition, time information, and driver information, and
- the objective variable includes at least one of a metric for each vehicle speed pattern and a metric for energy consumed.
Dependencies are inferred from the claim text.