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| """
CPD 市场 ROI 分析
基于 Straits/Stratview 市场数据
依赖:
pip install numpy matplotlib
"""
import numpy as np
market_data = {
2022: 80,
2023: 116,
2024: 169,
2025: 245,
2026: 356,
2027: 517,
2028: 750,
2029: 1035,
2030: 1420,
2034: 2500,
}
print("=" * 70)
print("CPD 市场分析与投资 ROI")
print("=" * 70)
print(f"\n{'年份':>6s} {'市场规模($M)':>14s} {'YoY增长':>10s} {'渗透率':>8s}")
print("-" * 42)
prev = None
for year, size in market_data.items():
if prev:
yoy = (size - prev) / prev * 100
else:
yoy = 0
pen = size / 50 / 80
print(f"{year:>6d} {size:>14.0f} {yoy:>9.1f}% {pen:>7.1%}")
prev = size
print(f"\n{'='*70}")
print("技术方案投资分析")
print(f"{'='*70}")
solutions = {
'60GHz FMCW': {
'rd_investment_m': 15,
'bom_per_unit': 20,
'price_per_unit': 50,
'market_share': [0.45, 0.35, 0.25, 0.20],
'units_m': [16, 20, 25, 30],
},
'UWB 雷达': {
'rd_investment_m': 25,
'bom_per_unit': 15,
'price_per_unit': 40,
'market_share': [0.10, 0.20, 0.30, 0.35],
'units_m': [4, 11, 30, 53],
},
'多传感器融合': {
'rd_investment_m': 40,
'bom_per_unit': 60,
'price_per_unit': 120,
'market_share': [0.10, 0.15, 0.20, 0.25],
'units_m': [4, 9, 20, 38],
}
}
print(f"\n{'方案':<18s} {'研发投入':>10s} {'BOM':>6s} {'售价':>6s} {'2026份额':>10s} {'2029份额':>10s} {'4年累计利润':>14s}")
print("-" * 80)
for name, s in solutions.items():
cumulative_profit = 0
for i in range(4):
revenue = s['price_per_unit'] * s['units_m'][i] * 1e6
cost = s['bom_per_unit'] * s['units_m'][i] * 1e6
profit = revenue - cost
cumulative_profit += profit
cumulative_profit -= s['rd_investment_m'] * 1e6
share_2026 = f"{s['market_share'][0]*100:.0f}%"
share_2029 = f"{s['market_share'][3]*100:.0f}%"
print(f"{name:<18s} ${s['rd_investment_m']:>8.0f}M ${s['bom_per_unit']:>4d} ${s['price_per_unit']:>4d} {share_2026:>10s} {share_2029:>10s} ${cumulative_profit/1e6:>12.1f}M")
print(f"\n{'='*70}")
print("CPD 供应链关键厂商")
print(f"{'='*70}")
supply_chain = {
'60GHz FMCW 芯片': ['Infineon', 'Texas Instruments', 'NXP', 'STMicroelectronics'],
'UWB 芯片': ['NXP (SR040)', 'Qorvo', '3DB Access', 'Apple (U1)'],
'IR 摄像头': ['OmniVision (OV2311)', 'Sony', 'OnSemi'],
'算法/AI': ['NOVELIC', 'Smarteye', ' Seeing Machines', 'Elliptic Labs'],
'系统集成': ['Continental', 'Bosch', 'Hyundai Mobis', 'ZF'],
}
for category, companies in supply_chain.items():
print(f"\n {category}:")
for c in companies:
print(f" • {c}")
|
