CN104859660B - 利用过去能量消耗中的变量预测电动车辆能量消耗 - Google Patents

利用过去能量消耗中的变量预测电动车辆能量消耗 Download PDF

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Publication number
CN104859660B
CN104859660B CN201510086943.5A CN201510086943A CN104859660B CN 104859660 B CN104859660 B CN 104859660B CN 201510086943 A CN201510086943 A CN 201510086943A CN 104859660 B CN104859660 B CN 104859660B
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energy expenditure
expenditure rate
energy
electric vehicle
variable
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CN104859660A (zh
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邱诗琦
詹森·迈尔
曾福林
桑吉萨·桑梅斯瓦兰
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Ford Global Technologies LLC
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Ford Global Technologies LLC
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    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/10—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles characterised by the energy transfer between the charging station and the vehicle
    • B60L53/14—Conductive energy transfer
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    • B60K35/20—Output arrangements, i.e. from vehicle to user, associated with vehicle functions or specially adapted therefor
    • B60K35/28—Output arrangements, i.e. from vehicle to user, associated with vehicle functions or specially adapted therefor characterised by the type of the output information, e.g. video entertainment or vehicle dynamics information; characterised by the purpose of the output information, e.g. for attracting the attention of the driver
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    • B60L15/2045—Methods, circuits, or devices for controlling the traction-motor speed of electrically-propelled vehicles for control of the vehicle or its driving motor to achieve a desired performance, e.g. speed, torque, programmed variation of speed for optimising the use of energy
    • B—PERFORMING OPERATIONS; TRANSPORTING
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    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
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Abstract

控制电动车辆的示例方法包括响应于所预测的能量消耗率而改变电动车辆的操作。该方法包括响应于过去能量消耗率中的变量而调整所预测的能量消耗。

Description

利用过去能量消耗中的变量预测电动车辆能量消耗
背景技术
本发明涉及预测电动车辆能量消耗以及尤其涉及利用过去能量消耗中的变量来提高预测。
由于电动车辆选择性地利用一个或多个电池供电的电机进行驱动，因此电动车辆总体上与传统机动车辆不同。相比之下，传统机动车辆仅依赖内燃发动机驱动车辆。电动车辆可以利用电机取代内燃发动机，或者电动车辆可以除了内燃发动机以外还使用电机。
示例电动车辆包括混合动力电动车辆(HEV)、插电式混合动力电动车辆(PHEV)、燃料电池车辆以及纯电动车辆(BEV)。电动车辆的动力传动***通常配备有具有电池单元的电池组，其中电池单元存储用于为电机提供动力的电力。电池单元可以在使用前充电。电池单元可以在行驶过程中通过再生制动或内燃发动机再次充电。
预测电动车辆能量消耗在例如评估电动车辆到能量耗尽的距离是有用的。一些电动车辆仅基于特定时间段所用能量的平均水平来预测能量使用，例如行驶的最后五英里、十五英里或者三十英里；或五分钟、十五分钟或一小时的行驶时间段。消费者可以在这些行驶英里或行驶时间段之间选择。
发明内容
根据本发明示例性方面的一种控制电动车辆的方法，除了其他方面以外包括响应于所预测的能量消耗率而改变电动车辆操作。该方法还包括响应于过去能量消耗率中的变量而调整所预测的能量消耗。
在上述方法的另一示例中，该方法包括响应于过去能量消耗率的平均水平而调整所预测的能量率。
在上述任一方法的另一示例中，该方法包括在调整过程中改变过去能量消耗率中的变量的权重。
在上述任一方法的另一示例中，该方法包括基于降低的荷电状态而增加过去能量消耗率中的变量的权重。
在上述任一方法的另一示例中，该方法包括基于降低的荷电状态而降低过去能量消耗率平均水平的权重。
在上述任一方法的另一示例中，过去能量消耗率是针对行驶距离的范围、时间或二者的车辆的能量消耗率。
在上述任一方法的另一示例中，该范围响应于来自电动车辆操作者的命令而可调整。
在上述任一方法的另一示例中，过去能量消耗率的变量包含过去能量消耗率的标准偏差。
根据本发明的一个实施例，基于所预测的能量消耗率而提供能量耗尽的预测距离。
根据本发明的一个实施例，随着电池荷电状态的降低而以非线性的方式降低能量耗尽的预测距离。
根据本发明的一个实施例，其中改变包含基于所预测的能量消耗率而选择路线行驶。
根据本发明的一个实施例，进一步包含响应于调整而扩大消费者可用荷电状态的范围。
根据本发明的另一示例的一种电动车辆，除了其他方面以外包括用于保持电动车辆过去能量消耗率范围的数据存储模块。控制器基于该范围内的变量来计算电动车辆的所预测的能量消耗。
在上述电动车辆的另一示例中，该范围内的变量包含范围的标准偏差。
在上述任一电动车辆的另一示例中，控制器进一步基于该范围内的过去能量消耗率的平均水平来计算电动车辆的所预测的能量消耗。
根据本发明的一个实施例，其中在计算过程中控制器根据电动车辆的电池荷电状态来区别地加权变量以及平均水平。
根据本发明的一个实施例，进一步包含用于接收输入的权重选择器模块，该权重选择器模块引起控制器在计算过程中区别地加权变量和平均水平。
根据本发明的一个实施例，进一步包含用于接收输入的范围选择器，该范围选择器调整范围的大小。
根据本发明的又一示例性方面的一种电动车辆，除了其他方面以外包括用于保持电动车辆过去能量消耗率范围的数据存储模块。包括控制器以基于该范围内的变量来计算电动车辆的所预测的能量消耗。
附图说明
所公开示例的各种特征及有利之处从具体实施方式中对本领域的技术人员而言是显而易见的。伴随具体实施方式的附图可以简要描述如下：
图1示意性地示出了示例电动车辆动力传动***；
图2以图表方式显示了贯穿具有图1中的动力传动***的车辆的一示例行驶周期的能量消耗；
图3以图表方式显示了具有图1中的动力传动***的车辆的另一个示例行驶周期的能量消耗；
图4示出了示例电动车辆的高度示意图；
图5示意性地示出了用于预测图4的电动车辆的能量消耗率的示例方法的流程；
图6以图表方式显示了当利用图5的方法预测能量消耗率时，在不同的电池电荷水平时的能量消耗率中的变量的示例权重；
图7示出了不同变量权的所预测的能量消耗率的示例覆盖范围；
图8以图表方式显示了利用过去能量使用中的变量的预测能量耗尽的距离如何与不利用过去能量使用中的变量的预测能量耗尽的距离不同。
具体实施方式
图1示意性地说明了用于电动车辆的动力传动***10。尽管此处描述为混合动力车辆(HEV)，但应理解的是，此处所描述的概念不限于HEV，并且可以扩展到其他电气化车辆，包括但并不限于插电式混合动力电动车辆(PHEV)、燃料电池车辆和纯电动车辆(BEV)。
在一个实施例中，动力传动***10是采用了第一传动***和第二传动***的功率分流动力传动***(powersplit powertrain system)。第一传动***包括发动机14和发电机18(即第一电机)的组合。第二传动***至少包括马达22(即第二电机)、发电机18以及电池组24。在这个示例中，第二传动***被认为是动力传动***10的电力传动***。第一和第二传动***产生扭矩用于驱动一组或者多组电动车辆的车辆传动轮28。
在本示例中是内燃发动机的发动机14以及发电机18可以通过动力传输单元30——例如行星齿轮组——连接。当然，也可以利用包括其它齿轮组和变速器的其它类型的动力传输单元来连接发动机14和发电机18。在一个非限制性实施例中，动力传输单元30是包括环形齿轮32、中心齿轮34以及支架总成36的行星齿轮组。
发电机18可以通过动力传输单元30由发动机14驱动以将动能转化为电能。作为选择，发电机18可以起到马达的作用以将电能转化成动能，从而向与动力传输单元30连接的轴38输出扭矩。由于发电机18可操作地连接于发动机14，发动机14的速度可由发电机18控制。
动力传输单元30的环形齿轮32可以与轴40相连接，轴40通过第二动力传输单元44与车辆传动轮28相连接。第二动力传输单元44可以包括具有多个齿轮46的齿轮组。其他动力传输单元也适宜。齿轮46将扭矩从发动机14传输到差速器48以最终为车辆传动轮28提供牵引力。差速器48可以包括能够向车辆传动轮28传输扭矩的多个齿轮。在这个示例中，第二动力传输单元44通过差速器48与轮轴50机械地耦接以向车辆传动轮28分配扭矩。
也可以采用马达22(即第二电机)通过向轴52输出扭矩而驱动车辆传动轮28，轴52也与第二动力传输单元44相连接。在一个实施例中，马达22以及发电机18相配合作为再生制动***的一部分，在该***中，马达22以及发电机18都可以作为马达输出扭矩。例如，每一个马达22以及发电机18都可以向电池组24输出电力。
电池组24是电动车辆电池总成的示例类型。电池组24的形式可以是能够输出电力以使马达22以及发电机18运行的高压电池。其他类型的能量存储装置和/或输出装置也可与具有动力传动***10的电动车辆一起使用。
具有动力传动***10的车辆的能量消耗率随着车辆行驶而改变。能量消耗率响应于影响能量消耗的变量而变化。影响能量消耗的示例变量包括但不限于车辆如何加速、车辆如何停止、道路等级、道路状况、行驶环境以及消耗能量的车辆附件。
过去能量消耗率常用于提供车辆的期望的或所预测的能量消耗率。所预测的能量率可以通过多种方式使用。例如，所预测的能量消耗率可用于评估车辆能量耗尽的距离(DTE)。通常，DTE评估等于可用能量除以所预测的能量消耗率。车辆操作者依赖DTE评估从而除了其他方面以外评估在不重新充电或不依赖内燃发动机的动力的情况下他们是否可以驾驶车辆到达期望的位置。
参照图2和图3，表100示出了第一行驶周期的能量消耗率R，并且表200示出了第二行驶周期的能量消耗率R。
针对距离X的第一行驶周期的平均(或中间)的能量消耗率A1与针对距离X的第二行驶周期的平均能量消耗率A2相同或基本相同。
值得注意的是，第一行驶周期的能量消耗率比第二行驶周期的能量消耗率的变化或摆动大。平均水平A1和A2不解释行驶周期中的变量。如果在不解释能量消耗率的变量的情况下，利用平均能量消耗率来计算所预测的能量消耗率，则第一行驶周期的所预测的能量消耗率将与第二个行驶周期的所预测的能量消耗率相同。
在这个示例中，车辆的能量消耗率响应于行驶周期中的变量而调整。即使平均水平A1和A2相同，但基于表100中的第一行驶周期的所预测的能量消耗率不同于基于表100中的第二行驶周期的所预测的能量消耗率。
第一行驶周期以及第二行驶周期中的能量消耗率中的变量可以利用标准偏差量化。变量表明在第一行驶周期和第二行驶周期中与各自的平均水平A1或A2的偏差程度。在这个示例中，表100的标准偏差会高于表200。
现在参照图4和图5，示例电动车辆300包括可操作地彼此连接的数据存储模块304、控制器308以及电池312。数据存储模块304保持电动车辆300的行驶周期的过去能量消耗数据，例如在图2和图3中图表地呈现的数据。数据存储模块304以及控制器308可以在车辆300内部、车辆300外部或二者都可以。
控制器308包括执行预测车辆300的能量消耗的程序的处理器316。该预测可用于提供例如车辆300的DTE评估。所预测的能量消耗至少部分基于车辆300过去能量消耗率范围内的变量。
处理器316编程为执行控制电动车辆300的方法320的一些或所有的步骤。示例方法320包括计算车辆300的过去能量消耗率中的变量的步骤326。在步骤330中，方法320响应于过去能量消耗率中的变量而调整车辆300的所预测的能量消耗。在步骤334中，方法320响应于调整而改变车辆300的操作。
在步骤330中，所预测的能量消耗率可以进一步响应于过去能量消耗率的平均水平或其他信息以及变量而调整。在一些示例中，方法320可以根据例如电池312变化的水平来改变车辆300的过去能量消耗率的权重相对于过去能量消耗率平均水平的权重。变量权重相对于平均水平权重的增加会增加变量在所预测的能量消耗率上的影响量。
在步骤334中，变化可以包括车辆行驶的不同路径、较不猛烈的行驶、计划路径的延伸、关闭某些***以保存能量等。如果，例如从步骤330中所预测的能量消耗表明在电池312不重新充电的情况下无法到达期望的目的地，步骤334可以包括在到达期望的目的地之前以不同的路径行驶到达充电站的建议。
在一个示例中，第一行驶周期的所预测的能量消耗率X利用如下的等式(I)计算：
等式(1)X＝μ+z′*σ。
在等式(1)中，μ表示在行驶周期过程中的平均能量消耗率，σ是在行驶周期过程中的能量消耗率的标准偏差，并且z′是σ的权重因子。车辆300的所预测的能量消耗率之后用于评估DTE。
在一些示例中，车辆操作者可以调整得知μ和σ的变化时的比率以及如何利用它们计算所预测的能量消耗率以及评估DTE。例如，操作者可以调整得知的消耗率从而更新车辆300行驶的每五英里、十五英里或五十英里。
当包含过去行驶周期能量使用中的显著变量时，能量消耗的预测通常更加保守。例如，利用带有变量的所预测的能量消耗所计算的DTE可以是针对在电池组24中的标称电荷量的100英里。相比之下，在利用不带变量的所预测的能量消耗所计算的DTE可以是针对在电池组24中的标称百分比电荷的95英里。
权重因子z′的值是可校准的并且可以基于能量利用的更保守或较不保守预测是否是期望的而设定权重因子z′的值。如图6中所示，z′的值可以基于电池组24中的荷电状态而变化。z′的值可以是电池组24中的荷电状态的函数。z′的值可以自动地调整，或者响应于操作者的输入而调整，或者二者皆可。
在这个示例中，DTE只有在荷电状态的较低范围时才保守。在荷电状态的较低范围时，通常存在里程焦虑的增加的可能性。更加保守的DTE有助于缓解这种里程焦虑。
在不同的荷电状态下，需要DTE计算解释不同的覆盖范围。覆盖范围代表其中消费者在能量耗尽之前行驶的英里数大于或等于显示的DTE数目的行程的期望概率。可以调整z′的值以确保获得这些覆盖范围。
参照图7的分布，例如，在消费者可用荷电状态(CSOC)是从百分之七十到百分之百时，DTE评估会要求如400所示的百分之五十的覆盖范围。当CSOC降低到百分之二十左右时，DTE评估会要求如404所示的百分之八十四的覆盖范围。当CSOC降低到百分之零左右时，DTE评估会要求如408所示的百分之九十八左右的覆盖范围。
在一些示例中，车辆操作者可以根据所需而调整z′的值。例如，操作者可以在更加保守的DTE和不太保守的DTE之间选择。更加保守的DTE将利用具有z′的权重值高于不太保守的DTE的所预测的能量消耗进行计算。
利用过去能量使用中的变量计算DTE的示例方法会有助于扩大电池组24的可用荷电范围(即CSOC范围)。参照图8，CSOC范围的示例是从百分之P1到P3的总电池荷电状态容量(BSOC)。这是用于计算响应于过去能量消耗率中的变量而调整的DTE的CSOC。可选地，范围从P1到P2的CSOC用于在不会响应于过去能量消耗率中的变量而调整的情况下计算DTE。
DTE附带-变量代表当DTE响应于过去能量消耗率中的变量而调整时在整个CSOC范围内的DTE。DTE不带-变量代表当DTE的计算不响应于过去能量消耗率中的变量而调整时在整个CSOC范围内的DTE。
从百分之P2到P3的荷电状态范围可以在限制操作策略(LOS)下使用。当计算DTE不带-变量时不包括荷电状态率的这部分。取而代之的是，即使总电池荷电状态容量仍然是百分之P2，但DTE是零，从而确保在DTE不带-变量是零之后仍留有一些范围。
示例DTE附带-变量是更加保守的(以及更加可靠的)。因此在较低的BSOC的情况下，可用的覆盖范围更多。当计算DTE附带-变量时因此会包括CSOC范围的LOS部分。在这个示例中，在计算过去能量使用时，通过结合变量，BSOC可以降低到少于百分之P2。同样，当CSOC的下限降低到低于BSOC的百分之P2，新的DTE计算会引起当电池组24完全充电时较高的DTE。
在一些示例中，CSOC的范围从总BSOC的百分之P1到百分之P3。所预测的能量消耗率X随着电池组24内的可用能量的降低而升高。当所预测的能量消耗率X增加并且开始依赖于在行驶周期过程中的能量消耗率的标准偏差时，示例DTE开始非线性地降低(在这个示例中是在百分之三十的BSOC时)。DTE变化时的比率随着CSOC接近百分之零而变慢。在CSOC为百分之零的情况下，DTE显示零英里的范围。
所公开的示例中的至少一些特征包括更加保守的DTE，该DTE可以降低操作者的里程焦虑。初始DTE在一些示例中也是增加的。
上述说明实质上是示例性的而并非限制。在没有脱离本发明的本质时，本发明示例的变形以及改变对本领域技术人员而言是显而易见的。因此，本发明的法律保护范围仅通过研究下面的权利要求而确定。

Claims (11)

1.一种控制电动车辆的方法，包含：
响应于所预测的能量消耗率而改变电动车辆的操作；以及
响应于过去能量消耗率中的变量而调整所预测的能量消耗率；
随着电池荷电状态的降低而以非线性的方式降低能量耗尽的预测距离。
2.根据权利要求1所述的方法，进一步包含响应于过去能量消耗率的平均水平而调整所预测的能量消耗率。
3.根据权利要求2所述的方法，进一步包含在调整过程中改变过去能量消耗率中的变量的权重。
4.根据权利要求3所述的方法，进一步包含基于降低的荷电状态而增加过去能量消耗率中的变量的权重。
5.根据权利要求3所述的方法，进一步包含基于降低的荷电状态而降低过去能量消耗率平均水平的权重。
6.根据权利要求2所述的方法，其中过去能量消耗率是针对行驶距离的范围的车辆的能量消耗率。
7.根据权利要求6所述的方法，其中范围响应于来自电动车辆操作者的命令而可调整。
8.根据权利要求1所述的方法，其中过去能量消耗率中的变量包含过去能量消耗率的标准偏差。
9.根据权利要求1所述的方法，基于所预测的能量消耗率而提供能量耗尽的预测距离。
10.根据权利要求1所述的方法，其中改变包含基于所预测的能量消耗率而选择路线行驶。
11.根据权利要求1所述的方法，进一步包含响应于调整而扩大消费者可用荷电状态的范围。
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