Value-moving deviation method for acquiring cycle-stage combustion parameters of engine based on multiple sensing signals

A value-moving deviation method for acquiring cycle-stage combustion parameters of an engine based on multiple sensing signals, comprising:

• S1, acquiring average values of combustion feature parameters of the engine under different working conditions as prior values by means of an engine bench experiment or simulation calculation, and storing the prior values by means of a mathematical model or a map table;
• establishing shape base models of key shape parameters of Weber equations of combustion heat release rate curves under different working conditions;
• and establishing a shape relation model of a correction relation between deviation values of the combustion feature parameters and the key shape parameters under each specific working condition;
• S2, looking up, according to current working condition information, the mathematical model or the map table storing the prior values of the combustion feature parameters to acquire the prior values of the combustion feature parameters under a current working condition, and obtaining the key shape parameters abase and mbase of the Weber equation of the combustion heat release rate curve under the current working condition from the shape base model;
• S3, reconstructing combustion feature parameter values based on signal features acquired by a plurality of sensors of the engine, calculating deviations between reconstructed values and the prior values of the combustion feature parameters separately, and determining a weight corresponding to each deviation by means of a probability distribution of the deviations, wherein a method for determining the deviation weight comprises:
• establishing a relation between experimental values and the prior values of the combustion feature parameters based on a deviation method:
• Y
• =
• X
• _
• +
• K
• i
• (
• X
• i
• -
• X
• _
• )
• ,
• wherein Y is the experimental value of the combustion feature parameters;
• Xi is the reconstructed value of an i-th combustion feature parameter, and is independent of each other;
• Ki is the deviation weight corresponding to Xi;
• and X is the prior value of the combustion feature parameters;
• and
• determining the deviation weight corresponding to the reconstructed value of each combustion feature parameter according to a method of a minimum variance of the experimental values of the combustion feature parameters;
• S4, performing, based on the determined deviation weight, a weighted summation on the deviations to obtain a fusion deviation of the combustion feature parameters as a real-time deviation amount of the combustion feature parameters, wherein
• a method for calculating the fusion deviation comprises:
• calculating the deviation between the reconstructed value and the prior value of each combustion feature parameter;
• then calculating the deviation weight corresponding to the reconstructed value of each combustion feature parameter;
• and performing weighted summation on all deviation values to obtain the fusion deviation as follows:
• Δ
• ⁢
• X
• =
• ∑
• i
• =
• 1
• n
• K
• i
• (
• f
• i
• (
• δ
• i
• )
• -
• X
• _
• )
• ,
• wherein ΔX is the fusion deviation, n is the number of types of sensing signals, and fi(δi) represents the reconstructed value of the combustion feature parameter corresponding to an i-th piece of sensing signal feature information;
• S5, correcting, according to the obtained real-time deviation amount, the prior values to obtain actual feature values;
• and
• S6, correcting, according to the actual feature values obtained in S5 and the shape relation model, the key shape parameters abase and mbase of the Weber equation obtained by means of the shape base model, and updating a mathematical expression of the combustion heat release rate curve to obtain each combustion parameter value under a current cycle.