Brazil
Salvador → Maceio
579 km (360 mi)
distance
7h 58m
drive time
Latest grid data on this route
Salvador · Brazil
- 63 g/kWh
- 91% renewable
- 26°C · hot
→
Maceio · Brazil
- 63 g/kWh
- 91% renewable
- 26°C · hot
Grid: Ember Climate · Weather: open-meteo.com
Range by Weather Condition
Our route data does not list any of the EV models we track as completing this route in normal weather. The charging-stop and time figures below are model estimates only.
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 hot climate of Salvador may slightly reduce range due to air conditioning use, but the terrain between these coastal cities is generally flat, which helps mitigate energy consumption. This route demands careful range management, as the sparse station coverage leaves little margin for error; a single missed or non-functional station could strand a driver far from the destination.