Engine calibration parameter optimization method based on automobile exhaust emission simulation environment

A technology for simulating environment and vehicle emissions, applied in neural learning methods, design optimization/simulation, special data processing applications, etc., can solve problems such as unavoidable, difficult to implement, and high cost

Active Publication Date: 2021-02-23
POLIXIR TECH LTD
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  • Abstract
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  • Application Information

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Problems solved by technology

The cost of a complete vehicle test is as high as tens of thousands, while parameter calibration is a sequential decision-making process of iterative optimization. To complete the calibration of an engine often requires hundreds of vehicle tests, which is costly and unavoidable
[0006] (2) Highly dependent on the experience of the calibration personnel
However, in the process of reinforcement learning, the process of a large amount of interactive trial and error between the agent and the ...

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  • Engine calibration parameter optimization method based on automobile exhaust emission simulation environment
  • Engine calibration parameter optimization method based on automobile exhaust emission simulation environment

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Embodiment Construction

[0028] Below in conjunction with specific embodiment, further illustrate the present invention, should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention, after having read the present invention, those skilled in the art will understand various equivalent forms of the present invention All modifications fall within the scope defined by the appended claims of the present application.

[0029] The engine calibration parameter optimization method based on the vehicle exhaust emission simulation environment mainly includes building a vehicle emission test simulation environment, evaluating the accuracy of the simulation environment, and searching for the optimal calibration parameters in the simulation environment. The construction of the vehicle emission test simulation environment is divided into simulation The driving strategy network of the driver; the driving strategy network o...

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Abstract

The invention discloses an engine calibration parameter optimization method based on an automobile exhaust emission simulation environment, and the method comprises the steps: (1) constructing an automobile emission test simulation environment based on machine learning, and (2) searching an engine calibration optimal parameter based on the simulation environment. Low-cost and high-efficiency optimization of engine calibration parameters of automobile exhaust emission in a simulation environment is realized. According to the method, the automobile engine parameters are optimized efficiently atlow cost in the simulation environment, and the technical effects of cost reduction and efficiency increase are achieved.

Description

technical field [0001] The invention relates to a method for optimizing engine calibration parameters based on simulation training. In a simulation environment based on machine learning technology, the vehicle exhaust emission process is simulated to obtain an optimization strategy for engine calibration parameters, which belongs to the field of industrial intelligent manufacturing. Background technique [0002] The vehicle engine calibration process adjusts the parameters of each control module in the electronic control unit to make the exhaust gas emitted during driving meet the national emission standards. After the engine, control strategy, and peripheral devices are determined, in order to make the vehicle's emissions meet the national standards, it is necessary to find out the parameters of the engine under working conditions. The general calibration process is first to make the engine work normally through the bench test, and then get the initial set of parameters. N...

Claims

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Application Information

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IPC IPC(8): G06F30/20G06N3/08
CPCG06N3/08G06F30/20
Inventor 秦熔均黄睿毛华奇彭万立
Owner POLIXIR TECH LTD
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