Nonlinear structure multi-link gap value identification method based on model correction thought
A technology of model correction and identification method, which is applied in the field of nonlinear system identification, can solve problems such as heavy workload, and achieve the effect of good noise resistance and good dynamic characteristics
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specific Embodiment 1
[0041] Specific embodiment 1: Nonlinear parameter identification of electric steering gear system considering multi-link gap
[0042]Step 1: Under different external torque amplitude conditions, step-sine frequency sweep experiments are performed on the electric steering gear system. The specific external excitation amplitude conditions are 1350N·mm, 2700N·mm, 4050N·mm, 5400N· mm and 6750N·mm, the sweep frequency range is 100-200Hz, the sweep frequency step is 0.1Hz, and the resonance frequency and common amplitude value of the electric steering gear system under different external torques are output, see Table 1.
[0043] Table 1 Experimental data of electric steering gear
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[0046] Step 2: Build the electromechanical coupling model of the electric steering gear system, such as figure 1 As shown, add clearance links in the ball screw-bearing model and the fork pair-sleeve model respectively, such as figure 2 and image 3 shown. The simulation condi...
specific Embodiment 2
[0076] Specific embodiment 2: objective function rationality verification
[0077] Steps 1 to 2 are the same as the specific embodiment 1.
[0078] Step 3: In order to verify the rationality of the objective function constructed in this patent, formula (1) and formula (2) are respectively used as the objective function to identify the nonlinear parameters of the electric steering gear system.
[0079] Step 4 is the same as the specific example 1.
[0080] Step 5: Substitute the gap values identified under the two objective functions into figure 1 The dynamic analysis is performed in the shown electric steering gear system, and the resonant frequency and common amplitude value data identified under different objective functions are output as shown in Table 4 and Table 5, and the comparison of resonance frequency and common amplitude value under different objective functions is drawn. Image 6 , Figure 7 shown.
[0081] Table 4 Comparison of resonance frequencies under di...
specific Embodiment 3
[0086] The specific embodiment three: the non-linear parameter identification method of the electric steering gear system considering the multi-link gap is the same as the specific embodiment one.
[0087] Step 3: Add artificial noise to the resonant frequency and common amplitude value data obtained from the experiment, namely
[0088] X E =X E (1+ηδ)
[0089] In the formula, X E is the resonant frequency vector or the common amplitude value vector; η is the noise level; δ is a standard normal distribution random vector with a mean of 0 and a variance of 1.
[0090] Set the noise level of the resonance frequency to 1% and the noise level of the common amplitude value to 5%. The comparison of the resonance frequency and the common amplitude value before and after adding noise is shown in Table 6.
[0091] Table 6 Resonance frequency and common amplitude after adding noise
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[0093] Step 4: Construct the objective function shown in formula (2) by using the exper...
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