On-line learning method for optimum running line of hybrid electric vehicle engine

Abstract

The invention discloses an online learning method for an optimal running line of a hybrid electric vehicle engine, which belongs to the technical field of hybrid electric vehicle energy efficiency optimization. The purpose of the present invention is to take the measurable engine speed in the hybrid power system as the correction amount, aim at the minimum fuel consumption, use the gradient descent algorithm to update and optimize the engine speed when the engine continues to output smoothly, and search in real time under the current power demand. The optimal operating point of the engine, so as to improve the fuel economy of the vehicle, is an online learning method for the optimal operation line of the hybrid electric vehicle engine. The steps of the invention are: an information collection module, an engine fuel consumption gradient estimation module, an OOL online learning process of the engine fuel consumption gradient, and a serial hybrid vehicle motor torque control module. The invention effectively improves the efficiency of online learning of the optimum operation curve of the automobile. Under the influence of environmental migration, aging and other factors, the engine can still provide more accurate OOL for the energy management system in real time, so as to ensure the optimal fuel economy of the vehicle.

Description

technical field [0001] The invention belongs to the technical field of hybrid electric vehicle energy efficiency optimization. Background technique [0002] The Optimal Operating Line (OOL) of the engine is a curve formed by connecting the operating points corresponding to the minimum fuel consumption rate under the same output power of the engine. In a hybrid vehicle, the vehicle distributes the power of the engine and the drive motor through energy optimization management according to the driving energy demand of the driver, so that the engine always runs near the economic operating point, thereby achieving the purpose of reducing the fuel consumption of the vehicle. Therefore, accurately obtaining the engine OOL is a prerequisite for implementing an efficient energy management strategy. Considering the influence of factors such as external environment changes and vehicle aging, the precise calibration of engine OOL has become a difficult problem in practical engineering....

AI Technical Summary

Problems solved by technology

Under the influence of external environment (temperature, air pressure) and engine aging and other factors, the actual OOL of the engine will drift to a certain extent near the original curve, and it is difficult to ensure the optimal fuel economy of the vehicle under the same energy management strategy

On the one hand, correcting the drifted OOL by off-line secondary calibration is a huge workload and difficult to realize; The design of the correction method brings great difficulties

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