柴油机朗肯循环余热回收系统的效率预测模型

Efficiency Prediction Model of a Diesel-Engine ORC Exhaust Heat Recovery System

有机朗肯循环(ORC)技术可以有效回收重型车用柴油机的排气热能。但在道路运行过程中,其排气热源不稳定,冷源的维持也需要消耗能量,使得蒸发压力和冷凝压力的在线优化与控制实施均存在严峻挑战。为此,建立了ORC余热回收系统的效率预测模型,以ORC系统的热力学第一定律模型为基础,抓住蒸发器阶跃响应的宏观特征,提出了有效换热量的动态修正模型,以及工况模式切换的预判因子,并采用简化机理和数据建模相结合的方法,建立了冷凝器散热功耗的经验模型;提出了基于效率预测模型的ORC余热回收系统优化控制架构及策略。道路仿真结果表明了效率模型和优化算法的有效性:ORC系统的有效做功时间达到94%,蒸汽过热度控制在5~15 K之间,冷凝器散热功耗与发电功率的比值维持在20%以下。

The ORC（organic Rankine cycle） system is regarded as one of the most potential ways for exhaust heat recovery of heavy-duty vehicle diesel engines. But the exhaust energy fluctuates widely during driving cycles, also the ORC cooling will introduce extra energy consumption. Consequently,it is a big challenge to optimize and control the evaporation pressure and condensation pressure in the driving cycle. To this end, a control-oriented ORC efficiency prediction model was completed at first： basing on a foundation model of the first law of thermodynamics; focusing on the dominant feature of the ORC system step response, an effective heat absorption dynamic model and operating modes corrected factor were built up; and an empirical model was established to describe the energy consumption for ORC cooling. Afterwards, a sequence optimization algorithm was proposed to seek optimum values of the evaporation pressure and condensation pressure dynamically. The validation results based on a simulation plat were encouraging： the effective working time percentage achieves94%, the superheat degree is controlled as 5~15 K, and the cooling power consumption is kept less than 20% of the ORC power generation.