Real-time predicting cruise control system based on economical driving

Abstract

The invention discloses a real-time predicting cruise control system based on economical driving. The real-time predicting cruise control system based on economical driving comprises an information collection module, a vehicle dynamics model establishing module and a receding horizon optimal calculation module, wherein the information collection module is used for collecting the driving state information, comprising speed information, the distance between a local vehicle and a front vehicle and the road traffic speed limiting information within the predicted distance, of the local vehicle and the front vehicle; the collected information is transmitted to the vehicle dynamics model establishing module; the vehicle dynamics model establishing module is used for establishing a vehicle dynamics model according to the collected traffic speed limiting information and the driving state information of the front vehicle and the local vehicle, establishing the control problem and determining the optimal objectives and satisfied constraint conditions; and the receding horizon optimal calculation module is used for obtaining the optimal gear sequence and an explicit solution of the optimal engine torque and braking force by optimizing through a method combing a Pontryagin minimum principle with a method of bisection on the basis of the control problem and the constraint conditions proposed by the vehicle dynamics model establishing module, and determining the optimal control rule.

Description

Technical field [0001] The invention belongs to the technical field of automobile intelligent assisted driving and energy control, and it relates to a real-time predictive cruise control (ED-PCC) system based on economical driving. It uses information such as forward traffic conditions and the speed of the preceding vehicle to improve Fuel economy of the whole vehicle while ensuring driving safety. Background technique [0002] Intelligent transportation, as the main development trend of urban transportation in the future, is valued by countries all over the world. The intelligence of the transportation system and the automation and intelligence of vehicle driving provide greater development space for vehicle driving optimization. Under the intelligent transportation system, relying on high-speed communication facilities and unified communication protocols, vehicle driving optimization is no longer a single vehicle trajectory planning, but a high-level system optimization based ...

AI Technical Summary

Problems solved by technology

As a result, the number of predicted steps is larger than other control systems, which leads to higher requirements for computational efficiency

Furthermore, due to the discrete gearbox ratios, the optimal control problem cannot be approximated as continuous, so it is a mixed integer nonlinear control problem

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