Driving range is one of the most important – and most scrutinized – factors in evaluating electric vehicles (EVs). However, it is also one of the hardest to predict. Range depends on a wide range of dynamic variables: driving behavior, road elevation, outside temperature, energy management strategy, and even passenger load.
For OEMs and Tier 1 suppliers, simulation has become a strategic tool to accurately estimate EV range during early development, long before physical testing begins. It enables a better understanding of how each condition affects energy consumption – helping teams design smarter systems, faster.
Why is range so hard to predict?
Unlike internal combustion vehicles, EV range is highly sensitive to external conditions and usage patterns. For example, an urban route with stop-and-go traffic may be more efficient than steady highway driving. Other influential variables include:
- Battery thermal management (heating or cooling)
- Use of auxiliary systems like HVAC or infotainment
- The driver’s style (aggressive vs. economical)
- Road gradient and vehicle load
These factors combine in complex, dynamic ways. Without simulation, it’s nearly impossible to understand or quantify their full impact early in development.
A predictive, multi-variable simulation approach
With a platform like SCANeR™, engineers can simulate how each factor contributes to overall energy usage and range. SCANeR™ supports:
- Detailed modeling of the powertrain: motor, inverter, battery, regenerative braking
- Realistic driving profiles: urban traffic, highway cruising, eco vs. aggressive driving
- Environmental conditions: ambient temperature, wind, road slope, humidity
- Simulation of in-vehicle electrical architecture: consumption, prioritization, energy loss
These variables are modeled together to form realistic usage scenarios, offering a comprehensive view of real-world EV performance.
Case study: how outside temperature impacts range
A typical simulation may show that EV range can drop by up to 30% in cold conditions. The reasons for this include:
- Increased energy draw from cabin heating systems
- Reduced battery efficiency in low temperatures
- Lower regenerative braking performance
Simulation allows engineers to quantify and isolate these effects, and explore solutions such as battery preconditioning or energy recovery improvements—before physical testing even begins.
Optimizing energy management strategies
Simulation also helps validate and improve onboard energy management strategies (EMS). These strategies govern how energy is allocated and prioritized across the vehicle systems. With SCANeR™, teams can:
- Compare multiple EMS logic options on identical driving routes
- Test real-time responses to different battery states of charge
- Evaluate how turning off non-critical systems improves range
This gives R&D teams the ability to optimize vehicle behavior in a controlled, reproducible environment.
Reducing development costs and improving technical decisions
Integrating simulation into EV development enables major benefits:
- Fewer physical prototypes required
- Improved early-phase design and energy efficiency tuning
- Detection of unrealistic or problematic operating modes
- Better alignment between battery sizing and real usage profiles
Simulation becomes a key decision-making tool that accelerates time-to-market while reducing costs and technical risks.
SCANeR™: a complete multi-physics environment for EV simulation
SCANeR™ is designed to support EV-specific challenges through:
- Integrated vehicle dynamics and energy consumption models
- Compatibility with third-party or custom battery and EMS models
- Realistic road, traffic, and environmental profiles
- HIL integration for closed-loop testing with physical ECUs
It offers a flexible and modular simulation ecosystem, tailored for both vehicle performance evaluation and energy strategy development.
