并联型混合动力汽车能量管理策略研究
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摘要
当混合动力汽车各部件的结构及性能特性确定后,整车的燃油经济性和排放水平取决于能量管理策略。目前混合动力汽车在如何通过能量管理策略的优化,最大程度地降低整车运行油耗,并对蓄电池荷电状态进行合理管理等方面还有待深入研究,因此开展能量管理策略研究对于降低混合动力汽车油耗和排放具有重要的理论意义和应用价值。本文完成了以下的研究内容
①建立了混合动力汽车多能源动力系统各部件数学模型;建立了驾驶员车速模糊控制模型,并考虑了汽车起步或换档过程中离合器对车速控制系统的减弱效果;建立了可用于仿真和实时控制的驾驶员需求驱动功率计算模型;建立了混合动力传动系统的动力学方程。在上述模型基础上,开发了基于前向仿真算法的并联型混合动力汽车性能仿真程序。
②在Kim等提出的并联型混合动力汽车等效模型基础上,建立了充电/放电工况下的混合动力系统充/放电综合效率模型。对于放电工况,提出了混合动力系统的放电综合效率最大为优化目标的瞬时能量管理优化策略,并引入再生制动能量回收影响系数来反映再生制动对能量管理策略的影响。研究表明随蓄电池荷电状态(State of Charge, SOC)降低,放电转矩界限上升。对于充电工况,针对蓄电池在不同SOC的充电需求以及充电效率,提出了3种瞬时能量管理优化策略,并获得了蓄电池在不同SOC下的充电转矩界限。
③提出了以制动时蓄电池充电条件下瞬时再生制动功率最大为主要优化目标,并在满足ECE制动法规的条件下减少车轮抱死机率,缩短制动距离的再生制动能量管理优化策略,获得了在不同蓄电池SOC、发电机转速、制动需求功率下的发电机再生制动优化转矩和前、后轮制动器制动转矩的计算方法。④提出了一种结合瞬时能量管理优化策略和蓄电池SOC管理策略,以减少汽车运行油耗为目标的能量管理策略。当混合动力汽车处于放电工况时,发动机和电动机的转矩分配仍采用瞬时放电综合效率优化控制策略,但针对循环工况初始蓄电池SOC值的不同,要求所设计的放电和充电控制策略能使汽车在循环工况结束时的SOC保持在不同的合理水平:对于循环工况初始蓄电池SOC值在其最佳范围内偏中高的,要求执行蓄电池SOC维持平衡策略;对于循环工况初始蓄电池SOC值在其最佳范围内偏中低的和小于最佳范围下限的,要求循环工况结束时SOC保持在其最佳范围内的偏中低值;对于循环工况初始蓄电池SOC值大于其最佳范围上限的,要求循环工况结束时SOC降到其初始值以下,但不低于SOC的最佳范围的上限,且初始SOC愈高,要求循环工况终了时的SOC下降得愈多。上述蓄电池SOC管理策略的目的是提高放电和充电控制策略适应汽车实际运行工况的负荷统计特征的能力,降低混合动力汽车的运行油耗。
当混合动力汽车处于充电工况时,发动机和发电机的转矩分配仍采用瞬时能量管理优化策略,但充电转矩界限根据汽车运行工况的负荷和车速统计特征进行设计。根据汽车运行工况的需求转矩分布密度和车速分布统计特征,得到充电工况切入的车速界限。提出了确定充电工况切入条件的方法:即设置不同的充电车速界限,以蓄电池SOC在某给定范围内充电后的循环工况油耗最小和循环工况终了时SOC值符合SOC管理策略要求为准测,得出合理的充电车速界限,确定蓄电池SOC在某给定范围内的充电控制策略。改变蓄电池SOC范围和充电车速界限,重复上述过程,最后获得蓄电池SOC在不同给定范围内的充电控制策略,该策略以蓄电池SOC、车速和/或充电转矩界限作为充电工况的转入条件。
轻度混合动力汽车在NEDC循环工况的燃油经济性仿真表明,与传统的基础车型比较,并联型轻度混合动力系统的燃油消耗显著降低。
⑤设计了基于dSPACE实时仿真系统快速控制原型技术的实时仿真控制主程序,完成了轻度混合动力传动系统控制试验研究。ISG启动发动机的实验表明电动机转速的模糊逻辑控制的稳定性好于PI控制。完成了混合动力传动系统从起步,连续换档加速,匀速到减速制动工况的控制实验,实验验证了所建立的混合动力汽车仿真模型的有效性。
The fuel economy and emission of hybrid electric vehicles (HEVs) are determined by the energy management strategy when the structure and characteristic of components are determined. The research on energy management strategy for HEVs plays important theoretical and application roles, and it needs to be researched thoroughly in the aspects about decreasing the fuel consumption to its best at driving mode and managing the state of charge (SOC) of battery reasonably. The study contents of this thesis are as follows
1) The mathematic models of components of multi-power sources system for HEVs were set up. The driver’s velocity control model with fuzzy logic was established, and the clutch’s effect on the velocity control system is take into account in the process of vehicle’s start up and gear shifting. The calculating model for driver’s demanded driving power was built for the applications in the simulation and real time control. The dynamic equations of hybrid powertrain were also built. Based upon the above models, the fuel economy and performance simulation program with forward–facing approach is developed for parallel HEVs.
2) Based upon the equivalent model of parallel HEVs proposed by Kim, the models of comprehensive charging/discharging efficiency for hybrid powertrain were built at the charging/discharging modes. The optimal instantaneous energy management strategy was proposed, with the goal of maximum of comprehensive discharging efficiency at the discharging mode, and the effect coefficient of regenerative braking energy recovery was introduced to reflect the effect of regenerative braking on the energy management strategy. The research shows that the discharging torque limits rises with the decline of battery SOC. Three kinds of optimal instantaneous energy management strategies were proposed at the charging mode, according to the different charging demands and efficiency at the different battery SOC, and the charging torque limits were get at the different battery SOC.
3) An optimal energy management strategy of regenerative braking was proposed, with the goal of maximum of the regenerative braking power of battery at the charging mode, and reducing the lock probability of wheels and shorting the braking distance under the condition for satisfying the braking regulation of ECE. The calculation methods about the optimal braking torque of generator, front and rear brake torques were get under the conditions of the different battery SOC, generator speed and demanded braking power.
4) Combined with the optimal instantaneous energy management strategy and battery SOC management strategy, an energy management strategy was proposed to reduce the vehicle’s fuel consumption at driving mode. For discharging mode, the optimal instantaneous energy management strategy was also applied to the torque distribution between engine and motor, but for different initial SOC of battery at the start point of driving cycle, it was demanded that discharging and charging control strategy should make the battery SOC maintain at the different reasonable levels: If the initial SOC is medium or high at its optimal range, then the charge-sustain strategy is implement. If the initial SOC is about low or medium, or lower to the minimum limit of its optimal range, then the battery SOC should be kept at the lower and medium of its optimal range at the end of driving cycle. If the initial SOC is higher than the maximum limit of its optimal range, it is requested that SOC at the end of the driving cycle should drop to the level below their initial value, but not lower than the upper limit of its optimal range, and the higher the initial SOC of battery is, the more decrease of SOC at the end of the cycle. The aim of the management strategy is to improve the ability of discharge/charge control strategy to adapt to the actual driving conditions of vehicle, and reduce fuel consumption of HEVs.
For charging mode, the optimal instantaneous energy management strategy is also applied to the torque distribution between engine and generator. The charging torque limits are redesigned according to the statistics characteristics of velocity and load of vehicle’s driving mode. According to the distribution density of demanded torque and velocity distribution at the vehicle’s driving mode, the velocity limits for entering charging mode were acquired. A method for deciding the entering condition of charging mode was proposed: that is, the reasonable charging velocity limits is chosen with the rules that the fuel consumption is minimum and the value of battery SOC at the end of cycle is satisfied by the demand of battery SOC management strategy, so that the charging control strategy at an certain scope is get. Changing the scopes of battery SOC and velocity limits, repeating the above process, finally the charging control strategies are got at the different scopes of battery SOC. The charging entering limits are determined by the battery SOC, velocity and / or charging torque limits.
The results of fuel economy simulation of a mild HEV at NEDC cycle shows that the decrease of fuel consumption is remarkable compared to the conventional vehicle.
5) The main control program of real-time simulation based on rapid control prototyping technology of dSPACE real-time simulation system was designed. The control tests of the mild hybrid powertrain were carried out. The experiments of engine starting by ISG show that the stability of motor speed with fuzzy logic control is better than that of PI control. The control experiment of the hybrid powertrain from start up, accelerating with continuous shifting, cursing and braking deceleration was also carried out. The test results verified the validity of the simulation model of the mild HEVs.
①建立了混合动力汽车多能源动力系统各部件数学模型;建立了驾驶员车速模糊控制模型,并考虑了汽车起步或换档过程中离合器对车速控制系统的减弱效果;建立了可用于仿真和实时控制的驾驶员需求驱动功率计算模型;建立了混合动力传动系统的动力学方程。在上述模型基础上,开发了基于前向仿真算法的并联型混合动力汽车性能仿真程序。
②在Kim等提出的并联型混合动力汽车等效模型基础上,建立了充电/放电工况下的混合动力系统充/放电综合效率模型。对于放电工况,提出了混合动力系统的放电综合效率最大为优化目标的瞬时能量管理优化策略,并引入再生制动能量回收影响系数来反映再生制动对能量管理策略的影响。研究表明随蓄电池荷电状态(State of Charge, SOC)降低,放电转矩界限上升。对于充电工况,针对蓄电池在不同SOC的充电需求以及充电效率,提出了3种瞬时能量管理优化策略,并获得了蓄电池在不同SOC下的充电转矩界限。
③提出了以制动时蓄电池充电条件下瞬时再生制动功率最大为主要优化目标,并在满足ECE制动法规的条件下减少车轮抱死机率,缩短制动距离的再生制动能量管理优化策略,获得了在不同蓄电池SOC、发电机转速、制动需求功率下的发电机再生制动优化转矩和前、后轮制动器制动转矩的计算方法。④提出了一种结合瞬时能量管理优化策略和蓄电池SOC管理策略,以减少汽车运行油耗为目标的能量管理策略。当混合动力汽车处于放电工况时,发动机和电动机的转矩分配仍采用瞬时放电综合效率优化控制策略,但针对循环工况初始蓄电池SOC值的不同,要求所设计的放电和充电控制策略能使汽车在循环工况结束时的SOC保持在不同的合理水平:对于循环工况初始蓄电池SOC值在其最佳范围内偏中高的,要求执行蓄电池SOC维持平衡策略;对于循环工况初始蓄电池SOC值在其最佳范围内偏中低的和小于最佳范围下限的,要求循环工况结束时SOC保持在其最佳范围内的偏中低值;对于循环工况初始蓄电池SOC值大于其最佳范围上限的,要求循环工况结束时SOC降到其初始值以下,但不低于SOC的最佳范围的上限,且初始SOC愈高,要求循环工况终了时的SOC下降得愈多。上述蓄电池SOC管理策略的目的是提高放电和充电控制策略适应汽车实际运行工况的负荷统计特征的能力,降低混合动力汽车的运行油耗。
当混合动力汽车处于充电工况时,发动机和发电机的转矩分配仍采用瞬时能量管理优化策略,但充电转矩界限根据汽车运行工况的负荷和车速统计特征进行设计。根据汽车运行工况的需求转矩分布密度和车速分布统计特征,得到充电工况切入的车速界限。提出了确定充电工况切入条件的方法:即设置不同的充电车速界限,以蓄电池SOC在某给定范围内充电后的循环工况油耗最小和循环工况终了时SOC值符合SOC管理策略要求为准测,得出合理的充电车速界限,确定蓄电池SOC在某给定范围内的充电控制策略。改变蓄电池SOC范围和充电车速界限,重复上述过程,最后获得蓄电池SOC在不同给定范围内的充电控制策略,该策略以蓄电池SOC、车速和/或充电转矩界限作为充电工况的转入条件。
轻度混合动力汽车在NEDC循环工况的燃油经济性仿真表明,与传统的基础车型比较,并联型轻度混合动力系统的燃油消耗显著降低。
⑤设计了基于dSPACE实时仿真系统快速控制原型技术的实时仿真控制主程序,完成了轻度混合动力传动系统控制试验研究。ISG启动发动机的实验表明电动机转速的模糊逻辑控制的稳定性好于PI控制。完成了混合动力传动系统从起步,连续换档加速,匀速到减速制动工况的控制实验,实验验证了所建立的混合动力汽车仿真模型的有效性。
The fuel economy and emission of hybrid electric vehicles (HEVs) are determined by the energy management strategy when the structure and characteristic of components are determined. The research on energy management strategy for HEVs plays important theoretical and application roles, and it needs to be researched thoroughly in the aspects about decreasing the fuel consumption to its best at driving mode and managing the state of charge (SOC) of battery reasonably. The study contents of this thesis are as follows
1) The mathematic models of components of multi-power sources system for HEVs were set up. The driver’s velocity control model with fuzzy logic was established, and the clutch’s effect on the velocity control system is take into account in the process of vehicle’s start up and gear shifting. The calculating model for driver’s demanded driving power was built for the applications in the simulation and real time control. The dynamic equations of hybrid powertrain were also built. Based upon the above models, the fuel economy and performance simulation program with forward–facing approach is developed for parallel HEVs.
2) Based upon the equivalent model of parallel HEVs proposed by Kim, the models of comprehensive charging/discharging efficiency for hybrid powertrain were built at the charging/discharging modes. The optimal instantaneous energy management strategy was proposed, with the goal of maximum of comprehensive discharging efficiency at the discharging mode, and the effect coefficient of regenerative braking energy recovery was introduced to reflect the effect of regenerative braking on the energy management strategy. The research shows that the discharging torque limits rises with the decline of battery SOC. Three kinds of optimal instantaneous energy management strategies were proposed at the charging mode, according to the different charging demands and efficiency at the different battery SOC, and the charging torque limits were get at the different battery SOC.
3) An optimal energy management strategy of regenerative braking was proposed, with the goal of maximum of the regenerative braking power of battery at the charging mode, and reducing the lock probability of wheels and shorting the braking distance under the condition for satisfying the braking regulation of ECE. The calculation methods about the optimal braking torque of generator, front and rear brake torques were get under the conditions of the different battery SOC, generator speed and demanded braking power.
4) Combined with the optimal instantaneous energy management strategy and battery SOC management strategy, an energy management strategy was proposed to reduce the vehicle’s fuel consumption at driving mode. For discharging mode, the optimal instantaneous energy management strategy was also applied to the torque distribution between engine and motor, but for different initial SOC of battery at the start point of driving cycle, it was demanded that discharging and charging control strategy should make the battery SOC maintain at the different reasonable levels: If the initial SOC is medium or high at its optimal range, then the charge-sustain strategy is implement. If the initial SOC is about low or medium, or lower to the minimum limit of its optimal range, then the battery SOC should be kept at the lower and medium of its optimal range at the end of driving cycle. If the initial SOC is higher than the maximum limit of its optimal range, it is requested that SOC at the end of the driving cycle should drop to the level below their initial value, but not lower than the upper limit of its optimal range, and the higher the initial SOC of battery is, the more decrease of SOC at the end of the cycle. The aim of the management strategy is to improve the ability of discharge/charge control strategy to adapt to the actual driving conditions of vehicle, and reduce fuel consumption of HEVs.
For charging mode, the optimal instantaneous energy management strategy is also applied to the torque distribution between engine and generator. The charging torque limits are redesigned according to the statistics characteristics of velocity and load of vehicle’s driving mode. According to the distribution density of demanded torque and velocity distribution at the vehicle’s driving mode, the velocity limits for entering charging mode were acquired. A method for deciding the entering condition of charging mode was proposed: that is, the reasonable charging velocity limits is chosen with the rules that the fuel consumption is minimum and the value of battery SOC at the end of cycle is satisfied by the demand of battery SOC management strategy, so that the charging control strategy at an certain scope is get. Changing the scopes of battery SOC and velocity limits, repeating the above process, finally the charging control strategies are got at the different scopes of battery SOC. The charging entering limits are determined by the battery SOC, velocity and / or charging torque limits.
The results of fuel economy simulation of a mild HEV at NEDC cycle shows that the decrease of fuel consumption is remarkable compared to the conventional vehicle.
5) The main control program of real-time simulation based on rapid control prototyping technology of dSPACE real-time simulation system was designed. The control tests of the mild hybrid powertrain were carried out. The experiments of engine starting by ISG show that the stability of motor speed with fuzzy logic control is better than that of PI control. The control experiment of the hybrid powertrain from start up, accelerating with continuous shifting, cursing and braking deceleration was also carried out. The test results verified the validity of the simulation model of the mild HEVs.
引文
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