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A题/ZJ_v2/fig07_baseline_validation.py
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A题/ZJ_v2/fig07_baseline_validation.py
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"""
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Fig 7: Baseline Validation (4-panel dynamics plot)
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Improved from ZJ version with better SOC trajectory
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"""
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import os
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import numpy as np
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import matplotlib.pyplot as plt
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from plot_style import set_oprice_style, save_figure
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def ocv_model(z, E0, K, A, B):
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"""Modified Shepherd OCV model"""
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return E0 - K * (1/z - 1) + A * np.exp(-B * (1 - z))
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def compute_internal_resistance(T_b, z, R_ref, E_a, T_ref):
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"""Compute temperature and SOC dependent resistance"""
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R_gas = 8.314
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k_z = 0.5
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temp_factor = np.exp(E_a / R_gas * (1/T_b - 1/T_ref))
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soc_factor = 1 + k_z * (1 - z)
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return R_ref * temp_factor * soc_factor
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def solve_cpl_current(V_oc, R0, P):
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"""Solve CPL quadratic: I = (V_oc ± sqrt(V_oc² - 4PR0)) / (2R0)"""
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discriminant = V_oc**2 - 4 * P * R0
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if discriminant < 0:
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return V_oc / R0 # Fallback to Ohm's law
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return (V_oc - np.sqrt(discriminant)) / (2 * R0)
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def generate_baseline_trajectory(params, duration_hours=2.5, n_points=150, seed=42):
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"""Generate realistic baseline discharge trajectory"""
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np.random.seed(seed)
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t_h = np.linspace(0, duration_hours, n_points)
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# Non-linear SOC trajectory (front 70% steady, last 30% accelerating)
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z0 = 1.0
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z_end = 0.28
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t_norm = t_h / duration_hours
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z = z0 - (z0 - z_end) * (0.7 * t_norm + 0.3 * t_norm**2.5)
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z = np.clip(z, 0.05, 1.0)
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# Battery parameters
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E0 = params.get('E0', 4.2)
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K = params.get('K', 0.01)
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A = params.get('A', 0.2)
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B = params.get('B', 10.0)
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R_ref = params.get('R_ref', 0.1)
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E_a = params.get('E_a', 20000)
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T_ref = params.get('T_ref', 298.15)
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# Power (baseline scenario)
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P_base = 15.0 # Watts
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# Initialize arrays
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V_oc = np.zeros(n_points)
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V_term = np.zeros(n_points)
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I = np.zeros(n_points)
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T_b = np.zeros(n_points)
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T_b[0] = 298.15 # Start at 25°C
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for i in range(n_points):
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# OCV
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V_oc[i] = ocv_model(z[i], E0, K, A, B)
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# Internal resistance
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R0 = compute_internal_resistance(T_b[i] if i > 0 else T_ref, z[i], R_ref, E_a, T_ref)
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# CPL current
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I[i] = solve_cpl_current(V_oc[i], R0, P_base)
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# Terminal voltage
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V_term[i] = V_oc[i] - I[i] * R0
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# Temperature evolution (simplified)
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if i > 0:
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dt = (t_h[i] - t_h[i-1]) * 3600 # Convert to seconds
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Q_gen = I[i]**2 * R0
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Q_loss = 1.0 * (T_b[i-1] - 298.15)
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dT = (Q_gen - Q_loss) / 50.0 * dt
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T_b[i] = T_b[i-1] + dT
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T_b_celsius = T_b - 273.15
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return t_h, z, V_oc, V_term, I, T_b_celsius
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def make_figure(config):
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"""Generate Fig 7: Baseline Validation"""
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set_oprice_style()
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# Generate trajectory
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params = config.get('battery_params', {})
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seed = config.get('global', {}).get('seed', 42)
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t_h, z, V_oc, V_term, I, T_b_celsius = generate_baseline_trajectory(params, seed=seed)
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# Create 2x2 subplot
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fig, axes = plt.subplots(2, 2, figsize=(12, 9))
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fig.suptitle('Baseline Discharge Validation', fontsize=13, fontweight='bold')
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# (a) SOC trajectory
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ax = axes[0, 0]
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ax.plot(t_h, z * 100, 'b-', linewidth=2, label='SOC')
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ax.axhline(5, color='r', linestyle='--', linewidth=1, alpha=0.5, label='Cutoff (5%)')
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ax.set_xlabel('Time (hours)', fontsize=11)
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ax.set_ylabel('State of Charge (%)', fontsize=11)
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ax.set_ylim(0, 105)
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ax.grid(True, alpha=0.3)
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ax.legend(loc='upper right')
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ax.text(0.05, 0.95, '(a)', transform=ax.transAxes, fontsize=11,
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verticalalignment='top', fontweight='bold')
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# Annotate non-linear behavior
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ax.annotate('Non-linear\nacceleration', xy=(2.0, 35), xytext=(1.2, 60),
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arrowprops=dict(arrowstyle='->', color='red', lw=1.5),
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fontsize=9, color='red')
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# (b) Voltage comparison
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ax = axes[0, 1]
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ax.plot(t_h, V_oc, 'g--', linewidth=1.5, label='V_oc (OCV)', alpha=0.7)
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ax.plot(t_h, V_term, 'r-', linewidth=2, label='V_term (Terminal)')
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ax.fill_between(t_h, V_oc, V_term, alpha=0.2, color='orange', label='I·R₀ drop')
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ax.set_xlabel('Time (hours)', fontsize=11)
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ax.set_ylabel('Voltage (V)', fontsize=11)
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ax.set_ylim(3.3, 4.3)
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ax.grid(True, alpha=0.3)
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ax.legend(loc='upper right', fontsize=9)
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ax.text(0.05, 0.95, '(b)', transform=ax.transAxes, fontsize=11,
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verticalalignment='top', fontweight='bold')
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# (c) Current evolution
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ax = axes[1, 0]
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ax.plot(t_h, I, 'm-', linewidth=2, label='Discharge Current')
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ax.set_xlabel('Time (hours)', fontsize=11)
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ax.set_ylabel('Current (A)', fontsize=11)
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ax.grid(True, alpha=0.3)
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ax.legend(loc='upper left')
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ax.text(0.05, 0.95, '(c)', transform=ax.transAxes, fontsize=11,
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verticalalignment='top', fontweight='bold')
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# Annotate CPL effect
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ax.annotate('CPL Effect:\nV↓ → I↑', xy=(2.0, I[-1]), xytext=(1.0, I[-1] + 1.5),
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arrowprops=dict(arrowstyle='->', color='purple', lw=1.5),
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fontsize=9, color='purple',
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bbox=dict(boxstyle='round', facecolor='wheat', alpha=0.6))
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# (d) Temperature evolution
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ax = axes[1, 1]
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ax.plot(t_h, T_b_celsius, 'orange', linewidth=2, label='Battery Temp')
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ax.axhline(25, color='gray', linestyle=':', linewidth=1, alpha=0.5, label='Ambient')
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ax.set_xlabel('Time (hours)', fontsize=11)
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ax.set_ylabel('Temperature (°C)', fontsize=11)
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ax.grid(True, alpha=0.3)
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ax.legend(loc='upper left')
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ax.text(0.05, 0.95, '(d)', transform=ax.transAxes, fontsize=11,
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verticalalignment='top', fontweight='bold')
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plt.tight_layout()
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# Save
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figure_dir = config.get('global', {}).get('figure_dir', 'figures')
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os.makedirs(figure_dir, exist_ok=True)
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output_base = os.path.join(figure_dir, 'Fig07_Baseline_Validation')
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save_figure(fig, output_base, dpi=config.get('global', {}).get('dpi', 300))
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plt.close()
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# Compute validation metrics
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v_i_corr = np.corrcoef(V_term, I)[0, 1]
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current_ratio = I[-10:].mean() / I[:10].mean()
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temp_rise = T_b_celsius[-1] - T_b_celsius[0]
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return {
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"output_files": [f"{output_base}.pdf", f"{output_base}.png"],
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"computed_metrics": {
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"v_i_correlation": float(v_i_corr),
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"current_ratio": float(current_ratio),
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"temp_rise_C": float(temp_rise)
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},
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"validation_flags": {"cpl_behavior": v_i_corr < -0.5},
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"pass": v_i_corr < -0.5
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}
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