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Automobile operation condition design method based on prior information and big data

A priori information and operating condition technology, applied in design optimization/simulation, electrical digital data processing, special data processing applications, etc., can solve problems such as inapplicable design methods for automobile operating conditions

Active Publication Date: 2018-04-13
JILIN UNIV
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Problems solved by technology

[0005] The purpose of the present invention is to provide a design method of vehicle operating conditions based on prior information and big data, using the big data of floating cars in the traffic system to design the operating conditions, aiming at the design of low-frequency big data, effectively solving the problem of When the working condition sampling frequency is less than 1Hz, the current vehicle operating condition design method is not applicable

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  • Automobile operation condition design method based on prior information and big data
  • Automobile operation condition design method based on prior information and big data
  • Automobile operation condition design method based on prior information and big data

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Embodiment Construction

[0080] The design method of the present invention is described in further detail through the following examples and accompanying drawings.

[0081] refer to figure 1 , the present invention is based on a priori information and a large data vehicle operating condition design method, including the following three stages, the specific implementation is described in detail as follows:

[0082] Phase 1: Determine the characteristic parameters that express the representativeness of the operating conditions

[0083] Determining the characteristic parameters that express the representativeness of the operating conditions mainly includes the following two steps:

[0084] 1) Determine the characteristic parameters of the speed according to the Markov chain ergodicity theory:

[0085] Markov chain at any time n ∈ T 1 The one-dimensional distribution of :

[0086] p(n)=p(0)P(n) (1)

[0087] In the formula, p(n) is n∈T at any moment in the Markov chain 1 When is the one-dimensional d...

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Abstract

The invention relates to an automobile operation condition design method based on prior information and big data. The method comprises the three stages that first, feature parameters expressing representativeness are determined; second, a typical condition database and a resampling database are used as prior condition databases, and states and state transfer information of the prior condition databases are subjected to statistical analysis to serve as prior information for condition design; and third, a new genetic algorithm based on the prior information is utilized to design conditions. Themethod is a new method which utilizes the big data with low sampling frequency to design the automobile operation conditions, and the problem that a current automobile operation condition design method is invalid to data with low sampling frequency lower than 1Hz is effectively solved.

Description

technical field [0001] The invention relates to a method for designing automobile operating conditions, in particular to a method for designing automobile operating conditions based on prior information and big data. Background technique [0002] With the development of positioning technology, mobile devices and the popularity of smart terminals, urban traffic generates massive amounts of data every day, and the data is increasing rapidly over time. In the context of big data represented by massive traffic information data, the use of floating vehicle collection technology in urban traffic systems to collect real-time operating status of taxis brings new opportunities for the design of urban working conditions. Compared with the microcosmic adjacent changes or even instantaneous changes of the data, the transportation department is more concerned about the macroscopic phenomena of the floating car data, such as traffic flow, so the collection frequency of the floating car is...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50
CPCG06F30/15G06F30/20
Inventor 施树明张曼林楠李文茹
Owner JILIN UNIV
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