【作者】 周楠；

【导师】 王庆年；

【作者基本信息】 吉林大学 ， 车辆工程， 2014， 博士

【摘要】 车用能源短缺和城市空气恶化的问题已对我国国民经济持续发展和人民身体健康产生了巨大的负面影响。为缓解上述问题，高效节能的新能源汽车技术和替代石油基的清洁代用燃料技术对实现能源高效利用与降低污染排放起着极为重要的作用。结合“十一五”国家“863”计划重大项目（2008AA11A140）“一汽解放牌混合动力客车新型整车技术开发”项目和“国家公派出国留学”项目期间本人在外的研究经历，对城市运行混合动力客车的控制算法和混合动力车用替代燃料进行研究。主要的内容包括：1.城市运行混合动力客车的循环工况分析根据混合动力客车在城市中运行工况的特点，针对不同类型的标准循环工况，应用均匀设计的优化方法，分析了循环工况的众多特征参数的关系。遴选出以车辆经济性评为价指标时，不同特征参数的相关度和权重指标。为后续制定控制算法时，对行驶路况的判别提供了重要的理论依据。2.基于模型预测算法的控制策略开发混合动力汽车的整体性能不仅仅依赖于各个独立部件的性能优劣，还很大程度上受到各个部件协调工作优劣程度的影响。本文将协调两动力源（发动机和电池）输出满足整车的功率需求，同时保证燃油的消耗最少定义为混合动力车辆的最优控制问题，针对非线性的混合动力车辆系统，提出基于模型预测控制算法，以优化的概念来解决混合动力汽车能量控制的最核心问题。相对于传统的控制算法，基于模型预测算法的控制策略能够提高车辆的燃油经济性并保持合理的电池核电状态（SOC）状态。3.基于GPS信息的模型预测算法车辆的未来能量需求，车辆的行驶状态都将会影响混合动力汽车的燃油消耗量。基于此，本文提出的能量控制算法结合了对车辆未来能量需求的预测。该能量预测算法基于GPS提供的信息和道路的交通状态，使用基于神经网络的模型识别方法，综合考虑车辆的驾驶环境，确定未来可能的能量需求水平。根据该能量需求水平，能控制算法将实时调整输入参数（如，发动机燃油消耗率、电池SOC、发动机转速等）的各个权重关系。利用均匀设计算法来优化不同能量需求下的运行权重系数。最后结合基于模型预测的能量控制算法和基于GPS信息的神经网络能量需求水平预测算法，提出了一种新的混合动力车辆的控制策略——基于GPS模型预测的控制策略，仿真结果证明了它的有效性。4.混合动力车用多醇复合燃料研究车用发动机的性能与整车控制算法的效果密切相关。为了进一步发挥混合动力车辆的节能减排特性，结合本人在国外的研究工作，基于多醇复合代用燃料燃烧特性的分析，对混合动力专用醇类燃料发动机开发和高效区的确定进行了相关分析。在定容燃烧室中对复合燃料的燃烧特性进行可视化研究，分析了传统工况和低温工况下燃料不同的燃烧特性。结果表明，在低环境温度并辅以高EGR比例的条件下，相比较传统的柴油，复合燃料表现出更高的燃烧效率和更低的排放特性。最后基于混合动力发动机，分析了在应用多醇复合燃料后，对混合动力车用发动机经济性和排放的影响。研究表明新的车用复合燃料具有进一步提高混合动力发动机经济性和排放性能的潜力。更多还原

【Abstract】 Regarding to the challenges of energy supply and environmental pollution, energy issuesand the deterioration of urban air environment have the tremendous negative impact onChina’s sustainable economy development and people’s health. The new automotivepower train and alternative clean fuel technologies could be as practical solution for thoseissues.Based on the “control strategy development for FAW Jiefang hybrid electric bus”(2008AA11A140) sponsored by the China “863project” and the “State-Sponsored StudyAbroad" sponsored by China scholarship council, control algorithms for hybrid electricbuses(HEB) and alternative fuels for hybrid electric bus have been studied in thedissertation. The main contents are as below:1. The analysis for HEB driving cycleAccording to hybrid buses which running in the city, uniform design optimization waschosen to analysis the characteristic characters for different types of standard drivingcycle. When selecting vehicle economy as the target function, evaluation of relevanceamong the different characteristic parameters of and weight indicators was carried out.Those provide a theoretical basis for the development of control strategy.2. Model predictive control strategy based control algorithms for HEBOverall, the performance of the hybrid vehicle is not only on the performance of themerits of each individual part, but also on the components coordination. Model predictionalgorithm is based on the model for multi-input output control loop optimization. Thealgorithm has a good control effect and robustness. Hybrid system is such a multi-inputoutput nonlinear system, so the proposed control approach is based on model predictivecontrol and trying to solve the HEV control problem by an optimization concept.Compared with the traditional control algorithm it can improve the fuel economy of thevehicle and maintain a reasonable battery state.3. GPS-based model predictive control strategyFuture energy demand of the vehicle and the state of vehicle will affect the fuelconsumption of a hybrid vehicle. So the proposed energy control algorithm combines thefuture energy needs using a prediction algorithm. The prediction algorithm is based ontraffic and road information provided by GPS, using of neural network model identification method, combing the driving conditions of the vehicle, the possible futureenergy needs could be obtained. According to the level of demand, energy controlalgorithm for real-time adjust the weight of input parameters, such as engine fuelconsumption rate, battery state (State Of Charge), engine speed, and so on. By thisalgorithm, the control strategy approach leads to improve the overall performance of thevehicle for further. Uniform design algorithm was used to find optimal weights fordifferent energy request. Model predictive control algorithm combined with energy levelof demand prediction using GPS information, we propose a new control strategy for ahybrid vehicle——GPS-based model predictive control strategy, and simulation resultsshow its effectiveness.4. Alcohol-diesel blends for HEB engineA new ABE (acetone-butanol-ethanol) and diesel blended fuel combustioncharacteristics was studied. For hybrid vehicle control, engine performance is a key partfor the whole strategy. The study shows that ABE and diesel blended can further improveHEB engine fuel economy and emissions. In the constant volume combustion chamber,visualization research on combustion characteristics of the blends under the conventionaldiesel engine operating conditions and low temperature conditions. Under Low ambienttemperature and supplemented with a high proportion of the EGR condition, compared toconventional diesel, the blends exhibits higher fuel combustion efficiency and loweremissions properties. Finally, based on a hybrid engine, the possible application for HEBengine on the economy and emissions is analyzed.更多还原