Brazil
Recife → Maceio
257 km (160 mi)
distance
3h 35m
drive time
21
EVs that complete it (estimated)
Latest grid data on this route
Recife · Brazil
- 63 g/kWh
- 91% renewable
- 27°C · hot
→
Maceio · Brazil
- 63 g/kWh
- 91% renewable
- 26°C · hot
Grid: Ember Climate · Weather: open-meteo.com
Range by Weather Condition
In normal weather 21 of 24 EV models complete this route. Estimated charging stops among them: 0 to 1 (median 0).
Select a vehicle above to explore weather-adjusted range.
☀️ Hot
Range estimate at ≥ 25 °C
🌤 Normal
Range estimate at 10-25 °C
❄️ Cold
Range estimate at < 10 °C
Assumptions behind these numbers
- Model assumptionStart charge 100%, arrive with 15% in reserve, charge up to 80% at each stop.
- Model assumptionUsable battery: 100% of each vehicle's listed capacity (the listed capacity may be gross or net; no correction is applied).
- Model assumptionSpeed: consumption starts from each vehicle's listed real-world efficiency, times a speed factor of 1.00 (1.00 = no speed adjustment).
- Vehicle dataWeather: each vehicle uses its own hot, normal and cold factor from our vehicle data, so consumption = efficiency x 1.00 / factor. Hot is 25 °C and above, normal is 10-25 °C, cold is below 10 °C.
- Model assumptionCharging speed: average power = min(vehicle peak kW, 150 kW cap) x 0.60 taper, plus 5 min per stop.
- MethodRange, energy and cost all use the same consumption figure. Energy is measured at the battery; charging losses are not included.
- MethodCharging stops are estimated from range and the charging window. They are not verified charging stations.
- Market dataCost: not shown, because no electricity market price is available for Brazil.
- Market dataCO2: energy x grid average carbon intensity of 63 g/kWh (Brazil, Ember Climate, Monthly average, April 2026, older than 45 days, last available value).
More EV Routes in Brazil
See all Brazil routes →Route analysis
The 257-kilometer drive from Recife to Maceio in Brazil takes approximately 215 minutes and is not a cross-border route. The terrain is likely coastal and flat, minimizing energy consumption from elevation changes.