File size: 3,654 Bytes
fcf8749 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 | """
EV Utilities for Phase 7.
Provides EV feasibility checks and charging overhead calculations.
"""
from typing import Optional
def is_route_feasible_for_ev(
battery_range_km: float,
route_distance_km: float,
safety_margin_pct: float = 10.0,
) -> bool:
"""
Check if a route is feasible for an EV driver.
Args:
battery_range_km: Driver's EV battery range in km
route_distance_km: Total route distance in km
safety_margin_pct: Safety margin percentage (default 10%)
Returns:
True if the route is within EV range with safety margin
"""
if battery_range_km <= 0:
return False
if route_distance_km is None or route_distance_km <= 0:
return True # No distance info, assume feasible
effective_range = battery_range_km * (1.0 - safety_margin_pct / 100.0)
return route_distance_km <= effective_range
def calculate_ev_charging_overhead(
route_distance_km: float,
battery_range_km: float,
charging_time_minutes: int,
penalty_weight: float = 0.3,
) -> float:
"""
Calculate effort overhead for EV drivers due to range/charging constraints.
Penalizes routes that use a high percentage of battery,
reflecting the mental/logistical burden of range management.
Args:
route_distance_km: Total route distance
battery_range_km: EV battery range
charging_time_minutes: Typical charging time
penalty_weight: Weight for penalty (default 0.3)
Returns:
Additional effort score for EV charging overhead
"""
if battery_range_km <= 0 or route_distance_km <= 0:
return 0.0
# Calculate usage ratio (0.0 to 1.0+)
usage_ratio = route_distance_km / battery_range_km
# Only penalize when usage exceeds 70% of range
if usage_ratio <= 0.7:
return 0.0
# Overhead increases as usage approaches or exceeds 100%
# More burden = more mental/planning effort
charging_overhead = (usage_ratio - 0.7) * charging_time_minutes * penalty_weight
return max(0.0, charging_overhead)
def get_ev_effort_adjustment(
driver_is_ev: bool,
battery_range_km: Optional[float],
charging_time_minutes: Optional[int],
route_distance_km: Optional[float],
safety_margin_pct: float = 10.0,
penalty_weight: float = 0.3,
) -> tuple[bool, float]:
"""
Get EV feasibility and effort adjustment for a driver-route pair.
Args:
driver_is_ev: Whether driver uses EV
battery_range_km: EV battery range (None for ICE)
charging_time_minutes: EV charging time (None for ICE)
route_distance_km: Route distance
safety_margin_pct: Safety margin for range check
penalty_weight: Weight for charging overhead
Returns:
Tuple of (is_feasible, effort_adjustment)
"""
if not driver_is_ev:
return (True, 0.0)
if battery_range_km is None or battery_range_km <= 0:
# EV without range info - assume feasible, no adjustment
return (True, 0.0)
if route_distance_km is None:
# No distance info - assume feasible, no adjustment
return (True, 0.0)
# Check feasibility
feasible = is_route_feasible_for_ev(
battery_range_km, route_distance_km, safety_margin_pct
)
if not feasible:
return (False, float('inf'))
# Calculate charging overhead
overhead = calculate_ev_charging_overhead(
route_distance_km,
battery_range_km,
charging_time_minutes or 30,
penalty_weight,
)
return (True, overhead)
|