96 lines
3.3 KiB
Python
96 lines
3.3 KiB
Python
import numpy as np
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from scipy.interpolate import interp1d
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class ControlSchedule:
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"""
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航空发动机控制计划 (Control Schedule)
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输入: PLA (角度 0~110)
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输出: Target NH, Target NL (0.0~1.0), Limit T5
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"""
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def __init__(self):
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# ==========================================
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# 1. 定义控制计划数据点
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# ==========================================
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# --- NH (高压转速) 计划 ---
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# 依据图片1：在 PLA=80 时达到 1.0
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# 0 -> 14.99: 0
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# 15.0 : 0.7
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# 80.0 : 1.0
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self._pla_nh = np.array([0.0, 14.99, 15.0, 80.0, 110.0])
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self._val_nh = np.array([0.0, 0.0, 0.70, 1.00, 1.00])
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# --- NL (低压转速) 计划 ---
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# 依据图片2：在 PLA=90 时达到 1.0
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# 0 -> 14.99: 0
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# 15.0 : 0.5
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# 90.0 : 1.0
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self._pla_nl = np.array([0.0, 14.99, 15.0, 90.0, 110.0])
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self._val_nl = np.array([0.0, 0.0, 0.50, 1.00, 1.00])
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# --- 限制值 (T5, P3) 计划 ---
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# 保持原有逻辑：在 PLA=100 时达到最大限制
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self._pla_lim = np.array([0.0, 14.99, 15.0, 100.0, 110.0])
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# Limit T5 (温度限制) [K]
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# 15度时1200K, 100度时1500K
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self._val_t5 = np.array([1200.0, 1200.0, 1200.0, 1500.0, 1500.0])
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# Limit P3 (压力限制) [kPa]
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# 15度时2000kPa, 100度时2500kPa
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self._val_p3 = np.array([800.0, 800.0, 2000.0, 2500.0, 2500.0])
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# ==========================================
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# 2. 构建插值函数
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# ==========================================
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self.f_nh = interp1d(self._pla_nh, self._val_nh, kind='linear', fill_value="extrapolate")
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self.f_nl = interp1d(self._pla_nl, self._val_nl, kind='linear', fill_value="extrapolate")
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self.f_t5 = interp1d(self._pla_lim, self._val_t5, kind='linear', fill_value="extrapolate")
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self.f_p3 = interp1d(self._pla_lim, self._val_p3, kind='linear', fill_value="extrapolate")
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def get_targets(self, pla):
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"""
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输入: pla (角度, 0.0 ~ 110.0)
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"""
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# 稍微做个限幅，防止超出定义域太多
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pla = np.clip(pla, 0.0, 110.0)
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t_nh = float(self.f_nh(pla))
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t_nl = float(self.f_nl(pla))
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l_t5 = float(self.f_t5(pla))
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l_p3 = float(self.f_p3(pla))
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return t_nh, t_nl, l_t5, l_p3
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# ==========================================
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# 自测代码
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# ==========================================
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if __name__ == "__main__":
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import matplotlib.pyplot as plt
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sch = ControlSchedule()
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# 测试关键点
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test_plas = [0, 10, 14.9, 15.0, 15.1, 57.5, 100, 105]
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print(f"{'PLA':<10} {'NH':<10} {'NL':<10}")
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print("-" * 30)
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for p in test_plas:
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nh, nl, _, _ = sch.get_targets(p)
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print(f"{p:<10} {nh:<10.4f} {nl:<10.4f}")
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# 画图确认阶跃形状
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x = np.linspace(0, 110, 500)
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y_nh = [sch.get_targets(i)[0] for i in x]
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plt.figure()
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plt.plot(x, y_nh, label='Target NH')
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plt.axvline(15, color='r', linestyle='--', alpha=0.5, label='Idle Point (15 deg)')
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plt.title("PLA to Engine Speed Schedule")
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plt.xlabel("PLA (Degree)")
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plt.ylabel("Normalized Speed")
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plt.legend()
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plt.grid(True)
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plt.show()
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