共查询到20条相似文献,搜索用时 203 毫秒
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针对单轴并联式混合动力汽车,以发动机万有特性和动力电池荷电状态(SOC)为依据,提出了基于能量平衡的逻辑门限的转矩分配控制策略。利用CVT传动系统传动比可连续变化的特性调整发动机工作在高效区,根据发动机万有特性图划分动力系统的工作区间,确定了各工作区间临界阈值参数,制定出整车动力系统控制规则,实时切换了动力系统的工作模式。在不同工作模式下通过确定发动机、驱动电机的最佳工作区对整车需求转矩进行了合理分配,达到提高动力系统的能量利用效率的目标。最后对具有相同动力系统的传统车和该混合动力汽车分别进行了经济性仿真,基于Cruise与Matlab/Simulink仿真平台对提出的转矩分配控制策略进行了联合仿真验证。仿真结果表明:基于能量平衡的逻辑门限的转矩分配策略能够在满足整车动力性的前提下,改善发动机的工作点,增加在高负荷区工作的概率,降低燃油消耗量,提高整车的经济性,并保持动力电池组SOC的波动在高效区内,提高了动力电池的充放电效率,延长其使用寿命。 相似文献
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《汽车安全与节能学报》2015,(1)
为保证纯电动轻型货车在具有最佳制动力分配的前提下多回收制动能量,仿真模拟了双能量源再生制动系统,设计了理想制动力分配再生制动控制策略。以东风EQ5030轻型货车为原型,根据纯电动轻型货车对能量和功率的双重要求,组成超级电容+蓄电池的双能量源储能结构。利用Matlab/Sumilink软件,建立再生制动系统仿真模型。在典型的道路循环工况下,对两种控制策略进行仿真对比。结果表明:本文设计的理想制动力分配再生制动控制策略比传统并联再生制动控制策略能量回收率提高了37.33%,增加了汽车的续驶里程。 相似文献
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秦大同杨官龙刘永刚林毓培 《汽车工程》2015,(12):1366-1370
基于插电式混合动力汽车(PHEV)可以通过外网充电的特性,选取发动机消耗燃油的成本与电机消耗电能的成本之和作为优化目标函数,采用庞特里亚金极小值原理进行优化仿真;研究了PHEV不同工作模式(电量消耗-电量维持模式和混合模式)对能耗经济性的影响;分析了行驶里程、电池荷电状态(SOC)初始值和能量价格比对能量分配控制策略的影响;最终制定了实时优化控制策略并与门限值控制策略进行对比仿真,结果表明,与门限值控制策略相比,采用制定的实时优化控制策略能耗经济性在不同的SOC初始值下都有大幅度的提高。 相似文献
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控制策略直接影响了串联混合动力汽车的燃油经济性、排放性以及车辆的续驶里程。文中基于WG6120HD混合动力城市客车动力系统。综述了蓄电池组SOC的估算方法以及对蓄电池容量的评价,并结合蓄电池组SOC的变化情况,对Plug—in串联式混合动力汽车控制策略进行了分析和研究。 相似文献
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针对串联式混合动力电动汽车的应用,基于PowerPC为核心的整车控制器硬件,成功移植eCos及其引导程序RedBoot,根据恒SOC的整车控制策略,编写串联式混合动力电动汽车整车控制器的软件系统,调节能量在蓄电池和电动机之间的合理分配,以实现较高的燃油经济性。通过dSPACE的实时仿真平台进行硬件在回路仿真,验证操作系统及应用程序的性能。 相似文献
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基于模糊控制理论,建立了某混合动力车再生制动控制策略.选取制动踏板位置、车速及电池SOC作为模糊控制器输入,设计了适于能量回收的制动力分配规则和模糊控制器.建立了电机、蓄电池和车轮动力学等模型,对不同初速下的再生制动进行了仿真.结果表明,基于模糊控制的制动力分配策略,不需要精确的数学模型,且有较好的鲁棒性和应用价值. 相似文献
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Using MATLAB/Simulink, we constructed a comprehensive simulation model for the fuel cell hybrid vehicle (FCHV) power train
in parallel with a power control strategy that uses a logic threshold approach implemented with a hybrid control unit (HCU).
The simulation implements power flow and power distribution under different vehicle operating modes using the accelerator
and decelerator pedal positions deduced from the driving schedule as primary inputs. The HCU control strategy also incorporates
regenerative braking and recharging for recovery of battery capacity. Using the D-optimality method for selection of the optimal
experiment values, three control threshold variables for the HCU are selected to maximize the hydrogen fuel economy under
certain driving cycles. The proposed method provides the optimal configuration of the FCHV model, which has the capability
of achieving the requested drive power while also meeting the vehicle driving schedule and recovery needs of the state of
charge (SOC) battery, with lower fuel consumption levels. 相似文献
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C. H. Zheng Y. I. Park W. S. Lim S. W. Cha 《International Journal of Automotive Technology》2012,13(3):517-522
The fuel economy of a fuel cell hybrid vehicle (FCHV) depends on its power management strategy because the strategy determines
the power split between the power sources. Several types of power management strategies have been developed to improve the
fuel economy of FCHVs. This paper proposes an optimal control scheme based on the Minimum Principle. This optimal control
provides the necessary optimality conditions that minimize the fuel consumption and optimize the power distribution between
the fuel cell system (FCS) and the battery during driving. In this optimal control, the final battery state of charge (SOC)
and the fuel consumption have an approximately proportional relationship. This relationship is expressed by a linear line,
and this line is defined as the optimal line in this research. The optimal lines for different vehicle masses and different
driving cycles are obtained and compared. This research presents a new method of fuel economy evaluation. The fuel economy
of other power management strategies can be evaluated based on the optimal lines. A rule-based power management strategy is
introduced, and its fuel economy is evaluated by the optimal line. 相似文献
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C. H. Zheng Y. I. Park W. S. Lim S. W. Cha 《International Journal of Automotive Technology》2012,13(6):979-985
Fuel cell hybrid vehicles (FCHVs) have become one of the most promising candidates for future transportation due to current energy supply problem and environmental problem. Fuel economy is an important factor in FCHVs. In order to properly evaluate the fuel economy of an FCHV, the initial battery state of charge (SOC) and the final battery SOC have to be identical so that the effect of the battery energy usage on the fuel economy is neglected. In the simulation or in the real driving, however, the final battery SOC is usually different from the initial battery SOC, and the final battery SOC often depends on the power management strategy. To consider the difference between the two battery SOC values, the concept of equivalent fuel consumption is presented by two methods. One is based on the relationship between delta SOC and delta fuel consumption, and the other is based on the optimal control theory. Two rule-based power management strategies for an FCHV are presented, and for each strategy, the fuel economy is evaluated based on the two methods. The characteristics of the two methods are discussed and compared, and the superior one is selected based on the comparison. 相似文献
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J. S. Kim S. M. Kim J. H. Jeong S. C. Jeong J. W. Lee 《International Journal of Automotive Technology》2016,17(5):865-872
In recent years, a hybrid electric vehicle (HEV) has been considered a successful technology. Especially, in case of a full HEV, the motor can drive the vehicle by itself at low velocity or assist the engine at high load. To improve the hybrid electric vehicle’s efficiency, a regenerative braking system is also applied to recover from kinetic energy. In this study, an experimental control apparatus was set up with a parallel hybrid electric vehicle mounted on a chassis dynamometer to measure ECU (engine control unit) and MCU (motor control unit) signals, including the current and state of charge in the battery. In order to analyze regenerative braking characteristics, user define braking driving cycle was introduced and carried out using different initial velocities and braking times. The FTP 75 driving cycle was then adapted under different initial SOC (state of charge) levels. The experiment data was analyzed in accordance with the vehicle velocity, battery current, instant SOC level, motor RPM, engine RPM, and then vehicle driving mode was decided. In case of braking driving cycle, it was observed that SOC were increased up to 1.5 % when the braking time and the velocidy were 6 second and 60 km/h, respectively. In addition, using the FTP 75 driving cycle, mode 1 was most frequently operated at SOC 65 conditions in phase 1. In phase 2, due to frequent stop-go hills, percentage of mode 1 was increase by 22 %. Eventually, despite of identity, it was shown that the characteristics of phase 3 differed from phase 1 due to the evanishment of the effects of initial SOCs. 相似文献
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为了优化混合动力汽车的能量动态分配过程,提升混合动力汽车的燃油经济性和动力电池荷电状态(SOC)平衡性,提高混合动力汽车能量管理策略的鲁棒性,以等效燃油消耗最小化策略为基础,结合对车辆未来行驶工况的预测研究,分析车辆未来行驶需求能量的变化,制定相应的动态调整策略。基于车联网通信技术,实时采集车辆的运行状态信息和交通信息,作为车辆未来工况预测模型的输入变量。以数据驱动为特征,基于混合深度学习建立工况预测模型。利用STL分解算法对各输入变量进行周期性、趋势性等特征分解,并对各输入变量的特征分量,使用混合深度学习网络从数据局部特征及时间维度依赖特征来深度挖掘目标车辆车速与外部信息及历史数据的关系,进而对车辆未来的行驶工况进行预测。利用预测的工况信息,分析车辆未来行驶需求能量的变化,应用于自适应等效消耗最小化策略等效因子的实时动态调整,从而实现对车辆的优化控制,并通过与传统自适应等效消耗最小化策略进行对比,验证该方法的有效性。研究结果表明:基于混合深度学习的工况预测模型预测精度比BP网络预测模型高44.72%;利用精确的预测工况信息预测能量管理,可以实时动态调整发动机和电机的功率输出,降低油耗并维持电池SOC平衡。 相似文献
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针对某功率分流混合动力汽车,探讨了既定模式转矩分配策略未知情况下全速域工作模式切换规则的优化问题。先在既定模式转矩分配策略未知的前提下,将等效燃油消耗与样本数字特征相结合,计算了不同荷电状态(SOC)值下各工作模式在所有可行工作点的基准综合燃油消耗率。以整车燃油经济性为优化目标,确定不同SOC值下所有可行工作点的最佳工作模式,进而得出基于车速、车轮端需求转矩、SOC值的优化后全速域工作模式切换规则,以满足不同工况下的工作模式选择需求。之后,不考虑模式切换过程对整车驾驶平顺性的影响,搭建了模式切换实施模型。再以4个新欧洲驾驶循环(NEDC)工况所构成的组合工况为目标行驶工况,将优化后全速域工作模式切换规则和传统基于逻辑门限的全速域工作模式切换规则分别应用于基于规则的能量管理策略,进行了整车燃油经济性仿真与台架试验验证。仿真结果表明:在不改变既定模式转矩分配策略的条件下,与基于逻辑门限的全速域工作模式切换规则情况相比,所提出的既定模式转矩分配策略未知情况下全速域工作模式切换规则优化方法至少可使整车燃油经济性提高7.33%。台架试验结果进一步表明,该优化方法至少可使整车燃油经济性提高6.17%。由此可见,所提出的既定模式转矩分配策略未知情况下全速域工作模式切换规则优化方法对整车燃油经济性具有较好的改善效果。 相似文献
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为了提高插电式混合动力汽车(PHEV)在电量保持下的燃油经济性,并解决插电式混合动力汽车在运行过程中动力元件效率对系统能量利用率影响的问题,制定了系统效率最优的控制策略。以PHEV关键动力部件的测试数据为基础,建立发动机、驱动电机、无级变速器(CVT)以及动力电池等关键部件的效率数值模型,并考虑了温度及荷电状态(SOC)对动力电池充放电功率的影响。设计以混合动力系统效率最优为适应度评价函数,将CVT速比、发动机转矩作为优化变量,以车速、加速度和SOC为状态变量,在动力性指标的约束下,运用遗传算法进行迭代寻优,PHEV的系统效率在第20代左右收敛于全局最优值。同时发动机转矩和CVT速比通过多代遗传进化,较快收敛于最佳值。将相关优化结果与车速、加速度拟合成相应的三维控制数表,综合数值建模和试验测试数据建模的方法,基于MATLAB/Simulink搭建插电式混合动力汽车整车控制策略仿真模型,采用新欧洲行驶循环工况进行仿真验证。结果表明:插电式混合动力汽车在电量保持模式下,利用遗传算法优化的系统效率最优控制策略相比优化前,动力电池SOC运行更为平稳,CVT效率有所提升,驱动电机及发动机转矩分配更为合理;百公里燃油消耗量从优化前的5.2 L降至4.5 L,燃油经济性提升了13.5%。 相似文献
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