Optimized Engine Strategies Cut Fuel Use in Range-Extended EVs
In the rapidly evolving landscape of automotive electrification, where environmental concerns and energy efficiency dominate engineering priorities, a new study has unveiled significant advancements in optimizing engine operation for range-extended electric vehicles (REEVs). As automakers strive to balance driving range, fuel economy, and emissions, researchers from GAC Automotive Research & Development Center have demonstrated that strategic refinements in how the onboard internal combustion engine operates can lead to measurable improvements in real-world fuel consumption.
The research, led by Chen Hong and Jiang Xiaoxiao, focuses on one of the most critical yet often overlooked aspects of REEV performance: the operational logic governing the range extender engine. Unlike conventional hybrids, where the engine directly contributes to vehicle propulsion, REEVs use their engines solely as generators, decoupling mechanical drive from electrical generation. This design freedom allows engineers to run the engine at its most efficient points, theoretically maximizing fuel-to-electricity conversion. However, the practical implementation of this principle involves complex trade-offs between system-level efficiency, battery cycling, power electronics losses, and dynamic driving demands.
Published in the peer-reviewed journal Chinese Internal Combustion Engine Engineering, the study leverages GT-SUITE, a high-fidelity simulation platform widely used in automotive development, to model a complete REEV powertrain system. The team constructed a detailed virtual prototype based on realistic vehicle parameters, including a curb weight of 1,550 kg, aerodynamic drag coefficient of 0.26, and a final drive ratio of 10.633. The simulation framework integrates models for the engine, generator, battery pack, power electronics, and vehicle dynamics, enabling a comprehensive analysis of energy flows throughout the entire system under standardized test conditions.
A central theme of the investigation is the comparison between two fundamental control paradigms: line operating conditions and point operating conditions. In the “line” strategy, the engine is permitted to operate across a continuous band of speeds and loads—specifically along the optimal efficiency curve of the combined range extender system, which includes both the engine and generator. This approach aims to keep the power generation subsystem running at peak thermodynamic efficiency at all times. In contrast, the “point” strategy restricts the engine to a discrete set of fixed operating points, typically defined by specific engine speeds and torque levels. While seemingly less flexible, this method offers tighter control over transient behavior, reduces wear, and simplifies calibration.
To evaluate these strategies, the team subjected the simulated vehicle to the China Light Vehicle Test Cycle (CLTC), a driving schedule designed to reflect typical urban and suburban driving patterns in Chinese cities. The CLTC features frequent stops, moderate accelerations, and relatively low average speeds, making it particularly relevant for assessing city-focused electric vehicles with range extenders. The simulations were conducted under charge-sustaining (CS) mode, meaning the battery’s state of charge (SOC) at the beginning and end of the cycle remained balanced at 30%, simulating real-world usage where the vehicle relies primarily on the range extender after the initial electric-only range is depleted.
The results revealed a clear advantage for point-based control strategies. When the engine was allowed to follow the optimal efficiency line without power constraints (Strategy 1), the simulated fuel consumption stood at approximately 0.041 L/km. Introducing upper or lower power limits to this line strategy yielded marginal improvements but failed to break below the 0.040 L/km threshold. However, when switching to point operation, fuel economy improved significantly. Among the various point strategies tested, Strategy 7—which constrained the engine to operate between 2,250 rpm and 2,500 rpm, with a minimum power output of 30 kW and a maximum of 38 kW—achieved the best result: a fuel consumption of just 0.03824 L/km, equivalent to 3.824 liters per 100 kilometers.
This improvement stems from a more favorable distribution of energy losses across the powertrain. Under line operation, especially at lower loads, the engine frequently operates at suboptimal speeds and torques, leading to higher relative losses in the engine itself and in the generator system. Additionally, because the power output is continuously variable, the system often generates excess electricity during low-demand phases, forcing the battery into frequent charge-discharge cycles. Each of these cycles incurs energy loss due to battery internal resistance and power converter inefficiencies.
Point strategies, by contrast, allow the engine to operate predominantly within a narrow, highly efficient band. Strategy 7, for example, saw the engine spend 82.91% of its runtime at 2,250 rpm producing 30.09 kW, a point where both engine thermal efficiency (42.49%) and overall range extender system efficiency (38.73%) are high. The remaining 17.09% of operation occurred at 2,500 rpm, generating 37.94 kW. This focused operation reduced engine-related losses by nearly 9 percentage points compared to the baseline line strategy and cut generator system losses by over 1 percentage point. Moreover, because the engine delivers power in larger, more predictable bursts, the battery experiences fewer partial cycles, reducing cumulative charging and discharging losses.
Interestingly, the study also examined a commonly assumed “optimal” strategy: fixing the engine to a single operating point—the absolute peak of the range extender system’s efficiency map (Strategy 8). Contrary to intuition, this approach performed worse than the multi-point Strategy 7, resulting in a fuel consumption of 0.03855 L/km, a degradation of 0.81% compared to the optimum. The reason lies in system rigidity. A single fixed point cannot adapt to varying power demands. During low-load driving, the engine continues to generate at its fixed high-power setting, flooding the system with excess electricity that must be stored, thereby increasing battery and converter losses. During high-power demand, the single-point engine may not deliver sufficient output, forcing the battery to compensate and discharge deeply, again incurring efficiency penalties. Thus, a degree of operational flexibility—even within a constrained point-based framework—proves essential for holistic system optimization.
Building on these findings, the research team explored the impact of enhancing the engine’s intrinsic performance. Recognizing that control strategy alone cannot overcome hardware limitations, they modeled a next-generation combustion system incorporating pre-chamber jet ignition and ultra-lean burn technology. This advanced configuration enables faster and more stable combustion under extremely lean air-fuel mixtures, allowing the engine to achieve higher brake mean effective pressure (BMEP) while maintaining optimal combustion phasing near top dead center. At 1,750 rpm, for instance, the optimized engine could produce 1.1 MPa BMEP compared to 0.8 MPa in the baseline version, with combustion duration slashed from 26.7 degrees to 14.3 degrees and the lean combustion limit extended from an excess air ratio of 1.4 to 2.3.
When this upgraded engine model was integrated into the simulation, the benefits were substantial. Reapplying the point-based control logic, the team found that even conservative powerband settings yielded better fuel economy than the previous best. Strategy 10, which set the engine’s operating range between 40 kW and 55 kW, achieved a remarkable fuel consumption of 0.03664 L/km—a 4.18% improvement over the original optimal case. This reduction translates to a real-world savings of roughly 0.16 L/100km, a meaningful figure in competitive markets where every fraction of a liter counts.
The energy flow analysis revealed that while the optimized engine incurred slightly higher generator system losses due to increased torque output, the gains in engine thermal efficiency were so pronounced that overall system losses decreased. Engine-related losses dropped from 140.76% of total output energy in the baseline case to 125.88% in the upgraded scenario. Although the reliance on battery buffering increased slightly—leading to higher battery and converter losses—the net effect was a significant reduction in total system inefficiency, bringing the overall loss ratio down from 172.25% to 162.14%.
These findings carry important implications for automakers developing range-extended electric vehicles. First, they challenge the notion that simply running an engine at its peak efficiency point is sufficient for optimal system performance. Instead, a more nuanced, multi-point strategy that accounts for battery and power electronics losses can yield superior real-world economy. Second, the study underscores the synergy between hardware and software optimization: improving the engine’s inherent efficiency amplifies the benefits of smart control logic, creating a compounding effect on fuel savings.
From a product development standpoint, the research suggests that future REEVs should employ adaptive point-based control schemes that dynamically select between two or three high-efficiency operating points based on real-time driving conditions and battery state. Furthermore, investing in advanced combustion technologies—such as pre-chamber ignition—is not merely an academic pursuit but a practical pathway to tangible efficiency gains. Such innovations allow the engine to produce more power in less time, reducing total runtime and minimizing cumulative losses across the entire energy chain.
The work also highlights the value of system-level simulation in modern automotive engineering. By modeling the interactions between engine, generator, battery, and vehicle dynamics, the researchers were able to identify non-intuitive trade-offs that would be difficult to detect through physical testing alone. This capability enables faster iteration, lower development costs, and more robust final calibrations.
For consumers, the implications are straightforward: smarter engine management and better engine design lead to longer effective range, lower fuel costs, and reduced emissions—all without compromising the smooth, responsive driving experience that defines electric mobility. As global markets continue to transition toward electrified transportation, solutions like the optimized REEV offer a pragmatic bridge, combining the convenience of liquid fuel with the efficiency and cleanliness of electric drive.
In conclusion, the study by Chen Hong, Jiang Xiaoxiao, and their colleagues at GAC provides a compelling blueprint for maximizing the efficiency of range-extended electric vehicles. By moving beyond simplistic control assumptions and embracing a holistic, system-wide approach to optimization, they demonstrate that meaningful improvements are still achievable in hybrid powertrains. Their work stands as a testament to the ongoing innovation within the internal combustion engine domain, proving that even in the age of electrification, the ICE remains a vital and evolving component of sustainable transportation.
Chen Hong, Jiang Xiaoxiao et al., Chinese Internal Combustion Engine Engineering, DOI: 10.13949/j.cnki.nrjgc.2024.04.005