Syngas deriving from biomass gasification is receiving increased interest as an alternative fuel in spark ignition (SI) engines for power generation, despite problems related to the variability of its composition and the low energy density. Syngas release from gasifiers is indeed strongly affected by the quality of the feedstock and by the specific features and control strategy of the reactor.

The paper considers the possibility to achieve, at the same time, high efficiency and low pollutant emissions of a syngas powered engine by acting on operating variables as the spark timing and the air-to-fuel ratio, with also the possible inclusion of exhaust gas recirculation (EGR). Model-based design and multi-objective optimization methods are applied as a feasible approach to address this issue, hence to improve the energetic and the environmental performances of power generation under a flexible fuel quality.

A one-dimensional (1D) model of a naturally aspirated SI engine fuelled by syngas, properly developed and validated through a specific experimental campaign, is here presented to investigate the effect of the main controlling variables on power output and emissions. A proper design of experiment (DoE) space is considered. The 1D model is coupled with a genetic optimization algorithm for the search of the best compromise solution between maximum performance and minimum pollutants amount. The identified optimal solution allows a reduction up to the 50% for both nitrogen oxides and carbon monoxide emissions with a negligible worsening of the power output.

尽管存在与组成可变性和低能量密度有关的问题，但源自生物质气化的合成气作为发电用火花点火（SI）发动机的替代燃料受到越来越多的关注。从气化炉中释放出的合成气的确受到原料质量以及反应器的特殊功能和控制策略的强烈影响。

本文考虑了通过同时作用于火花正时和空燃比的工作变量来实现合成气动力发动机的高效率和低污染物排放的可能性，同时也可能包括废气再循环（EGR）。基于模型的设计和多目标优化方法被用作解决该问题的可行方法，从而在灵活的燃料质量下提高了发电的能量和环境性能。

本文介绍了通过合成气驱动的自然吸气式SI发动机的一维（1D）模型，并通过特定的实验活动对其进行了适当开发和验证，以研究主要控制变量对功率输出和排放的影响。考虑适当设计实验（DoE）空间。一维模型与遗传优化算法结合在一起，用于在最大性能和最小污染物量之间寻找最佳折衷解决方案。确定的最佳解决方案可以将氮氧化物和一氧化碳的排放量降低多达50％，而功率输出的恶化却可以忽略不计。