The quest for sustainable mobility has placed the electric car at the forefront of automotive innovation. Among the various technological pathways, the extended-range electric vehicle (EREV) represents a compelling solution, designed to mitigate range anxiety by incorporating an internal combustion engine (ICE) that acts solely as a generator, or “range extender,” to recharge the battery pack when its state of charge (SOC) is low. While this architecture promises the zero-tailpipe-emission benefits of a pure battery electric car for most daily trips, the intermittent operation of its ICE inevitably introduces pollutant and greenhouse gas emissions. Understanding the real-world performance of such an electric car under diverse driving conditions is critical for accurate environmental impact assessments and for refining energy management strategies. This article, based on experimental findings, delves into the fuel consumption and emission characteristics of an extended-range electric car under different traffic scenarios, with a focus on low-battery-state operation.
Urban traffic is characterized by high variability, oscillating between free-flowing conditions and severe congestion during peak hours. This variability significantly influences vehicle operation modes. For a conventional vehicle, congestion leads to frequent stops, idling, and low-speed creeping, which typically degrades fuel economy and can elevate certain emissions. However, for an extended-range electric car, the relationship between vehicle speed and engine operation is decoupled. The engine-generator set operates based on the vehicle’s power demand and battery SOC, not directly on wheel torque. This unique characteristic prompts a fundamental question: how do different traffic scenarios—morning rush hour, evening rush hour, and unobstructed flow—affect the fuel consumption and emissions of an extended-range electric car when it is operating in its charge-sustaining (low SOC) mode?
Methodology: Assessing the Electric Car on Real Roads
To investigate this question, a comprehensive real-driving emission (RDE) test campaign was conducted. The subject was a China-6 emission standard compliant extended-range electric car. Its key specifications are summarized in Table 1.
| Parameter | Value / Specification |
|---|---|
| Vehicle Type | Extended-Range Electric Car (EREV) |
| Curb Mass | 2520 kg |
| Powertrain | Dual-motor all-wheel drive |
| Front Motor Power | 130 kW (max) |
| Rear Motor Power | 200 kW (max) |
| Range Extender Engine | 1.5L, 4-cylinder, Direct Injection |
| Engine Rated Power | 113 kW |
| Aftertreatment System | Three-Way Catalyst (TWC) |
| Battery Initial SOC for Tests | 15% (Low Battery State) |
A Portable Emissions Measurement System (PEMS) was employed to gather second-by-second data. The system integrated modules for measuring gaseous pollutants (CO, CO₂, NO, NO₂ via NDIR and NDUV techniques), particulate number (PN) via diffusion charging principle, exhaust mass flow, GPS data, meteorological conditions, and vehicle OBD parameters (e.g., engine speed, coolant temperature).
The core of the experiment involved repeating the same urban route (approximately 23 km in Tianjin, China) under three distinct traffic scenarios, each starting with a low battery state of 15% SOC:
- Morning Rush Hour (MRH): Representing congested conditions with frequent stops.
- Unobstructed Traffic (UO): Representing free-flowing conditions with minimal stops.
- Evening Rush Hour (ERH): Representing severely congested conditions.
The ambient conditions and trip characteristics for each test are detailed in Table 2. Notable differences include the initial engine coolant temperature and the resulting trip dynamics, characterized by parameters like Relative Positive Acceleration (RPA) and the 95th percentile of the product of velocity and positive acceleration (v·apos[95]). The unobstructed run exhibited more aggressive driving dynamics, while the morning rush hour was the most gentle.
| Parameter | Morning Rush Hour (MRH) | Unobstructed (UO) | Evening Rush Hour (ERH) |
|---|---|---|---|
| Initial Coolant Temp. | 40 °C | 25 °C | 25 °C |
| Avg. Ambient Temp. | 19.3 °C | 22.6 °C | 17.8 °C |
| Trip Distance | 22.78 km | 23.26 km | 23.26 km |
| Trip Duration | 3421 s | 2717 s | 3829 s |
| Average Speed | 23.97 km/h | 30.82 km/h | 21.87 km/h |
| Urban RPA (m/s²) | 0.19 | 0.30 | 0.23 |
| Urban v·apos[95] (m²/s³) | 8.72 | 17.68 | 12.78 |
Results and Analysis: Fuel Economy and Emissions
The aggregate results, calculated according to standard RDE data evaluation methods, revealed striking trends. The fuel consumption and carbon dioxide (CO₂) emissions were highest during congested peak hours, while pollutant emissions (NOx, CO, PN) were paradoxically highest during the unobstructed scenario. This electric car, when operating with a low battery, demonstrated a significant sensitivity to traffic patterns.
| Metric | Morning Rush Hour (MRH) | Unobstructed (UO) | Evening Rush Hour (ERH) |
|---|---|---|---|
| Fuel Consumption (L/100km) | 11.08 | 9.45 | 11.38 |
| CO₂ Emissions (g/km) | 260.7 | 221.7 | 248.9 |
| NOx Emissions (mg/km) | 165 | 459 | 361 |
| CO Emissions (mg/km) | 445 | 579 | 589 |
| PN Emissions (10⁹ #/km) | 762 | 900 | 1000 |
The data shows that this extended-range electric car in low-SOC mode exhibits high fuel consumption overall, comparable to many conventional vehicles of similar mass. The superior fuel and CO₂ economy during unobstructed driving can be attributed to the engine operating more frequently within its high-efficiency zone due to a more stable and higher power demand for charging. Congestion, with its low average speed and frequent low-power demands, forces the engine to operate less efficiently or to shut down more frequently, but the energy required for frequent starts and low-load operation harms the overall fuel economy.
The emission results, however, tell a different story. The highest pollutant levels were recorded during the unobstructed drive. To understand this counterintuitive finding, a deeper analysis of cumulative and transient emissions is required.
Cumulative Emission Profiles and the Cold-Start Effect
Normalized cumulative emission profiles revealed that a disproportionate share of total trip pollutants was emitted during the initial cold-start phase (defined here as the period before the engine coolant reached 70°C). This is a critical insight for the environmental assessment of such an electric car.
For NOx, the cold-start contribution was approximately 75% of the total trip emissions in the unobstructed test, 43% in MRH, and 61% in ERH. For PN, the contributions were 65% (UO), 15% (MRH), and 45% (ERH). CO emissions also showed significant cold-start shares. The variance is partly linked to the different initial coolant temperatures (40°C for MRH vs. 25°C for UO and ERH). A warmer initial condition significantly reduces cold-start emissions, which explains why MRH, despite being congested, had the lowest overall pollutant numbers—it benefited from a warmer start. The relationship can be conceptualized by considering the light-off temperature of the TWC. The conversion efficiency η for pollutants before light-off is near zero. The total mass of pollutant *m_p* emitted during a cold-start phase can be approximated by integrating the engine-out emission rate over the time *t_cs* until catalyst light-off:
$$
m_{p, cs} = \int_{0}^{t_{cs}} \dot{m}_{p, engine}(t) dt
$$
where $\dot{m}_{p, engine}(t)$ is high due to enriched fueling for start and catalyst heating strategies.
If we exclude the cold-start phase (data after coolant >70°C), the emission picture changes, as shown in Table 4. With the dominant cold-start influence removed, the unobstructed scenario now shows the lowest hot-running NOx and CO emissions, aligning better with expectations of more efficient engine operation. However, PN emissions during hot operation were highest for the severely congested ERH scenario, suggesting that frequent engine stops and restarts under low-temperature conditions (even post warm-up) can generate significant particulate events.
| Metric | Morning Rush Hour (MRH) | Unobstructed (UO) | Evening Rush Hour (ERH) |
|---|---|---|---|
| NOx Emissions (mg/km) | 94.07 | 85.35* | 138.54 |
| CO Emissions (mg/km) | 249.74 | 162.01* | 254.36 |
| PN Emissions (10⁹ #/km) | 172.29 | 134.62 | 253.39 |
| CO₂ Emissions (g/km) | 206.91 | 172.29 | 254.36 |
| *Calculated from derived total and cold-start contribution data. | |||
Transient Analysis: Engine Strategy and Emission Peaks
A second-by-second analysis of engine speed and emissions provides the final layer of understanding. Despite the decoupled nature of the drivetrain in this electric car, the traffic scenario profoundly influenced the engine charging strategy.
During unobstructed driving, the engine exhibited a higher frequency of start-stop events (engine speed = 0 for 38.9% of the time vs. ~32.7% for peak hours) and operated at higher speeds (>2000 rpm for 8.5% of the time vs. 1.3-3.4% for peak hours). In free-flow conditions, the vehicle system likely aimed to recharge the battery more aggressively to prepare for potential high power demands, leading to higher engine load points. In congestion, the frequent but low power demand for creeping did not justify frequent engine stops or high-load operation; the engine often remained idling or at low load to meet the immediate low power need.
The transient emission traces pinpoint the moments of high pollution. Major emission peaks occurred during two key events:
- Cold Start: The initial high-emission phase due to a cold engine and inactive TWC.
- Hot Restart and Load Transients: Significant NOx peaks occurred during hot restarts after a prolonged engine stop, likely due to cooled-down exhaust system components reducing TWC efficiency. CO peaks were closely tied to engine speed/load transients. During rapid increases in engine speed to meet a charging power demand, the air-fuel ratio control can momentarily deviate from stoichiometry, causing rich spikes and high CO emissions. This was particularly pronounced during the unobstructed drive’s aggressive charging strategy. The instantaneous CO emission rate $\dot{m}_{CO}$ can be modeled as a function of the deviation from the ideal air-fuel ratio (AFR):
$$
\dot{m}_{CO} \propto f(\lambda), \quad \text{where } \lambda = \frac{AFR_{actual}}{AFR_{stoich}}
$$
During transients, $\lambda$ dips below 1 (rich mixture), causing a sharp, non-linear increase in $\dot{m}_{CO}$.
Discussion: Implications for the Extended-Range Electric Car
The findings highlight the complex environmental footprint of an extended-range electric car when its internal combustion range-extender is active. The primary advantage of this electric car architecture—eliminating tailpipe emissions during battery-electric operation—is balanced by the challenge of managing the emissions from its onboard generator.
Firstly, the low-battery-state fuel consumption is a critical metric. The results indicate that operating this electric car in charge-sustaining mode in dense urban traffic can lead to fuel economy worse than that of some efficient hybrids, negating one of the key benefits of electrification for that portion of the journey. This underscores the importance for users of such an electric car to maintain adequate battery charge through regular plug-in charging to maximize electric driving and minimize range-extender use, especially in cities.
Secondly, the dominant role of cold start cannot be overstated. For the extended-range electric car, the engine may start cold multiple times throughout a day if the battery is depleted. Each cold start emits a large pulse of pollutants. Strategies to reduce this impact are essential, such as:
- Minimizing the number of cold starts by altering the energy management strategy to run the engine for longer, continuous periods once started, even at slightly sub-optimal efficiency.
- Implementing rapid catalyst heating strategies (e.g., post-injection, delayed ignition).
- Utilizing exhaust thermal management to retain heat between short engine operating cycles.
Thirdly, the traffic-scenario-dependent engine strategy is a key finding. The vehicle’s control unit modulates the range-extender’s operation based on perceived power demand, which is indirectly linked to traffic flow. The more aggressive charging in unobstructed traffic, while good for fuel economy, led to high pollutant emission factors due to demanding transients. This presents an optimization challenge: calibrating the energy management system not just for efficiency but also for minimal emissions under all anticipated driving patterns. A more predictive strategy, possibly using navigation and traffic data, could smooth engine operation and reduce harmful transients.
Conclusion
This investigation into the real-world performance of an extended-range electric car under varying traffic scenarios reveals a nuanced picture. While the electric car’s drivetrain decouples engine operation from wheel torque, traffic conditions significantly influence the range-extender’s operation strategy and, consequently, its environmental impact.
Key conclusions are:
- An extended-range electric car operating with a low battery state exhibits relatively high fuel consumption, which is further exacerbated by traffic congestion.
- Free-flowing traffic yields the best fuel and CO₂ economy for this electric car in charge-sustaining mode, but it can also produce the highest total trip pollutant emissions due to a pronounced cold-start effect and aggressive engine transients associated with its charging strategy.
- The cold-start phase and engine restart/load-transient events are the primary sources of pollutant emissions (NOx, CO, PN) for the range-extender, highlighting a critical area for technological improvement.
- The energy management system of an extended-range electric car tailors the engine’s charging behavior to the driving scenario, leading to different emission profiles. Congestion leads to fewer but potentially less efficient engine stops/starts, while free-flow conditions trigger a more dynamic engine strategy focused on rapid battery replenishment.
For policymakers, these results emphasize that the environmental benefit of an extended-range electric car is highly contingent on usage patterns. Promoting adequate charging infrastructure to enable regular battery charging is as important as the vehicle technology itself. For engineers, the challenge lies in developing more sophisticated thermal and energy management systems that co-optimize for efficiency, drivability, and ultra-low emissions across the entire spectrum of real-world driving, ensuring that the extended-range electric car fulfills its promise as a genuinely cleaner mobility solution.