Abstract
Methanol/diesel RCCI combustion has emerged as a promising high-efficiency, ultralow-emission strategy for the sustainable development of diesel engines under carbon neutrality targets. This study experimentally investigates the coupled effects of excess air coefficient (λ) and altitude (0-2000 m) on combustion characteristics and emissions in a methanol-diesel RCCI (MD-RCCI) engine under low and medium operating conditions. Results show that decreasing λ can enhance the combustion of relatively lean mixtures, significantly reducing total hydrocarbon (THC) emissions. At 1400 rpm-25% load, reducing λ from 3.5 to 2.0 lowered THC emissions by 46.0%, 42.5%, and 34.1% at 0, 1000, and 2000 m, respectively. At 1800 rpm-50% load, decreasing λ from 2.25 to 1.5 further reduced THC emissions by 64.2%, 68.6%, and 68.7% across the same altitudes. As λ decreases, the peak in-cylinder pressure declines, while the peak cylinder temperature and exhaust gas temperature (EGT) gradually rise. The peak heat release rate (HRR) increases at low load but decreases at medium load. However, an excessively low λ leads to markedly retarded combustion phasing and elevated NOx, soot, and particulate number (PN) emissions. With increasing altitude at fixed λ, ignition delay lengthens and both peak pressure and HRR decrease, whereas peak temperature and EGT increase. THC emissions declined by 21.0% (low load) and 16.4% (medium load) from 0 to 2000 m, while NOx emissions slightly rise due to higher combustion temperatures. In contrast, soot and PN emissions increase owing to deteriorated air-fuel mixing and incomplete combustion under oxygen-deficient high-altitude conditions. The influence of λ and altitude on CO emissions shows load-dependent responses. At low load, CO emissions first increase and then decrease with decreasing λ (peaking near λ = 2.5) and rise with altitude (up to +46.7% at λ = 2.75). At medium load, CO emissions consistently decrease with both richer mixtures and higher altitude (average reduction of 6.0%). These findings provide quantitative insights for optimizing the MD-RCCI engine calibration across varying altitude environments and support its practical deployment in real-world applications.