MODEL-BASED PREDICTIVE CONTROL OF AN ELECTRIC VEHICLE
The invention relates to a model-based predictive (MPC) control of an electric vehicle. It is notably directed to a method that comprises: executing an MPC algorithm (13) involving a high-level solver module (13.1), a longitudinal vehicle dynamics model (14), and a cost function (15) that is associa...
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creator | HUG, Markus, Stephan DOMAHIDI, Alexander LEFKOPOULOS, Vasilis |
description | The invention relates to a model-based predictive (MPC) control of an electric vehicle. It is notably directed to a method that comprises: executing an MPC algorithm (13) involving a high-level solver module (13.1), a longitudinal vehicle dynamics model (14), and a cost function (15) that is associated with the high-level solver module (13.1). The high-level solver module (13.1) is executed during a current route section, by taking into account the longitudinal vehicle dynamics model (14) to calculate a longitudinal trajectory (31) mini-mising the cost function (15), for the electric vehicle (1) to travel over a prediction horizon in accordance with the calculated cost function. The cost function (15) contains a first term (16) describing an amount of energy (-EBat) to be supplied by a battery (9) of the electric vehicle (1) over the prediction horizon in accordance with the calculated longitudinal trajectory (31), the battery (9) serving as an energy store for an electric machine (8) for driving the electric vehicle (1). It further contains a second term (17) describing a travel time deviation percentage (Tt) between a predicted travel time (tp) and a minimum travel time (tmin). The predicted travel time (tp) describes how long the electric vehicle (1) re-quires to travel over the prediction horizon according to the calculated longitudinal trajectory, while the minimum travel duration (tmin) describes a minimum time period which the electric vehicle (1) requires to travel over the prediction horizon. |
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It is notably directed to a method that comprises: executing an MPC algorithm (13) involving a high-level solver module (13.1), a longitudinal vehicle dynamics model (14), and a cost function (15) that is associated with the high-level solver module (13.1). The high-level solver module (13.1) is executed during a current route section, by taking into account the longitudinal vehicle dynamics model (14) to calculate a longitudinal trajectory (31) mini-mising the cost function (15), for the electric vehicle (1) to travel over a prediction horizon in accordance with the calculated cost function. The cost function (15) contains a first term (16) describing an amount of energy (-EBat) to be supplied by a battery (9) of the electric vehicle (1) over the prediction horizon in accordance with the calculated longitudinal trajectory (31), the battery (9) serving as an energy store for an electric machine (8) for driving the electric vehicle (1). It further contains a second term (17) describing a travel time deviation percentage (Tt) between a predicted travel time (tp) and a minimum travel time (tmin). 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It further contains a second term (17) describing a travel time deviation percentage (Tt) between a predicted travel time (tp) and a minimum travel time (tmin). The predicted travel time (tp) describes how long the electric vehicle (1) re-quires to travel over the prediction horizon according to the calculated longitudinal trajectory, while the minimum travel duration (tmin) describes a minimum time period which the electric vehicle (1) requires to travel over the prediction horizon.</abstract><oa>free_for_read</oa></addata></record> |
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language | eng ; fre ; ger |
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subjects | ELECTRIC EQUIPMENT OR PROPULSION OF ELECTRICALLY-PROPELLEDVEHICLES ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES, IN GENERAL MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES PERFORMING OPERATIONS TRANSPORTING VEHICLES IN GENERAL |
title | MODEL-BASED PREDICTIVE CONTROL OF AN ELECTRIC VEHICLE |
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