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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 achieves 94％,the superheat degree is controlled as 5～15 K,and the cooling power consumption is kept less than 20％ of the ORC power generation.