谭丕强,李二峰,胡志远,楼狄明.增程器发动机的喷油策略优化[J].内燃机工程,2019,40(5):52-57.
增程器发动机的喷油策略优化
Injection Strategy Optimization of Auxiliary Power Unit Engine for an Electric Vehicle
DOI：10.13949/j.cnki.nrjgc.2019.05.008
关键词:增程器  模型拟合  喷油策略  排放
Key Words:auxiliary power unit  model fitting  injection strategy  emission
基金项目:国家科技支撑计划项目（2014BAG06B01）
作者单位
谭丕强,李二峰,胡志远,楼狄明 同济大学 汽车学院，上海 201804 
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摘要:为了研究轨道压力、主喷正时、预喷正时及预喷油量这4个主要喷油参数对增程式电动汽车增程器（APU）发动机有效燃油消耗率和NOx 排放特性的影响，根据APU发动机不同工况下的运行特点，结合整车功率需求及所匹配发电机的最佳工作区域，采用多工况点模式的基础控制策略，选取3个稳态工况点为APU发动机的运行工况。之后基于空间填充+V最优设计方法采用混合试验方案，利用二阶多项式回归模型+径向基函数（RBF）神经网络模型建立发动机性能和排放拟合模型。给出APU发动机的性能优化约束条件和优化目标，利用法线-边界交集优化算法（NBI）进行油耗最低和NOx 排放最低的双目标优化，确定了3个稳态工况点的最佳喷油策略。结果表明各工况点在优化后的有效燃油消耗率平均降低了4.03%，NOx 排放平均降低了30.51%。
Abstract:In order to study the effect of rail pressure, main injection timing, pre-injection timing and pre-injected fuel amount on the fuel consumption and NOx emission characteristics of the auxiliary power unit(APU) engine for an electric vehicle, according to the operating characteristics of the APU engine under different operating conditions, together with the vehicle's power demand and optimal operating area of the matched generator, the basic control strategy of multi-mode was adopted, and three steady-state operating points were selected as the operating conditions of the APU engine. Then, based on the space filled+V optimal design method, the hybrid test was adopted, and an engine performance and emission fitting model was established by using the regression calculation and neural network model. Under the given conditions of engine performance optimization conditions and optimization objectives, the normal boundary intersection optimization method was used to optimize the double target with minimum fuel consumption and NOx emissions, and the optimal fuel injection strategy for three steady-state operating points was determined. Results show that compared to the original engine, the optimized fuel consumption of each mode is reduced by 4.03% on average, and the average NOx emissions is reduced by 30.51%.
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