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公开(公告)号：US20180340784A1
公开(公告)日：2018-11-29
申请号：US15606791
申请日：2017-05-26
Applicant: Ford Global Technologies, LLC
Inventor： Devesh Upadhyay , Michael Brendan Hopka
CPC classification number: G01C21/3469 , F01N3/023 , F01N3/0238 , F01N3/027 , F01N9/002 , F01N9/007 , F01N2900/0402 , F01N2900/102 , F01N2900/12 , F01N2900/1606 , F02D41/00 , G01C21/3415 , G01C21/3484 , G01C21/3492 , G01C21/3611 , G01C21/3617 , G01C21/3691
Abstract: Methods and systems are provided for maintaining a database with details of frequently travelled routes and selecting a travel route for a vehicle from the database based on particulate filter regeneration requirements. In one example, a method may include selecting one or more routes from the database based on a current particulate filter soot level, fuel efficiency, travel time, operator behavior, etc., ranking the routes based on the particulate filter regeneration efficiency of each of the one or more routes. At vehicle key-off, the database may be updated with information regarding the travelled route including a level of particulate filter regeneration achieved during the drive cycle.
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公开(公告)号：US20160201532A1
公开(公告)日：2016-07-14
申请号：US14592617
申请日：2015-01-08
Applicant: Ford Global Technologies, LLC
Inventor： Timothy Brian Chanko , James Robert Warner , Douglas Allen Dobson , Devesh Upadhyay
IPC: F01N3/023
CPC classification number: F01N3/0232 , F01N3/023 , F01N9/002 , F01N2430/00 , F01N2430/02 , F01N2900/08 , F01N2900/10 , F02D41/0087 , F02D41/029 , F02D2200/0812 , F02D2200/10 , F02D2200/701 , Y02T10/47
Abstract: Systems and methods are described for coordinating the regeneration of a gasoline particulate filter to a time duration when engine output falls below a predetermined load threshold selected to indicate a low power state of the engine. In one particular example, the engine is configured to adjust engine operations to regenerate the particulate filter responsive to engine output falling below a predetermined low power threshold, the regeneration further based on an estimated duration that the output falls continuously below the low power threshold. The system and methods described advantageously allow for either full or partial regeneration events to be performed based on the estimated duration of the engine output below the low power threshold.
Abstract translation: 描述了用于协调汽油微粒过滤器的再生的发动机输出低于预定负载阈值以选择以指示发动机低功率状态的持续时间的系统和方法。 在一个特定示例中，发动机被配置成调整发动机操作，以响应于低于预定低功率阈值的发动机输出而再生微粒过滤器，再生进一步基于输出连续低于低功率阈值的估计持续时间。 所描述的系统和方法有利地允许基于低于低功率阈值的发动机输出的估计持续时间来执行全部或部分再生事件。
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公开(公告)号：US09381468B2
公开(公告)日：2016-07-05
申请号：US14248875
申请日：2014-04-09
Applicant: Ford Global Technologies, LLC
Inventor： Frank Korpics , Dean Pennala , Devesh Upadhyay , Hao Wu
CPC classification number: B01D53/9495 , B01D53/9431 , F01N3/2066 , F01N9/00 , F01N11/00 , F01N2560/026 , F01N2610/02 , F01N2900/1402 , F01N2900/1616 , F01N2900/1621 , Y02T10/24 , Y02T10/47
Abstract: Systems and methods for detecting ammonia slip in an exhaust system based upon transient NOx sensor responses are described. In one example method, an exhaust system allocates tailpipe NOx sensor output to NOx and NH3 levels responsive to the transient sensors using a segment length method that processes the transient signals based on the total segment lengths calculated within a window. A ratio of segment lengths relative to a threshold is determined for a measured and expected NOx rate of change downstream of an SCR that is further used to determine a probability of NOx and NH3 based on the measured sensor activities, and a controller is included to adjust one or more parameters based on the allocation and changes of sensor output.
Abstract translation: 描述了基于瞬态NOx传感器响应来检测排气系统中氨滑移的系统和方法。 在一个示例性方法中，排气系统使用使用基于在窗口内计算的总段长度来处理瞬态信号的段长度方法来响应于瞬态传感器而将尾管NOx传感器输出分配给NO x和NH 3水平。 确定段长度相对于阈值的比率，用于SCR的下游的测量和预期的NOx变化率，其进一步用于基于测量的传感器活动来确定NOx和NH 3的概率，并且包括控制器以调整 基于传感器输出的分配和变化的一个或多个参数。
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公开(公告)号：US20140301925A1
公开(公告)日：2014-10-09
申请号：US14248875
申请日：2014-04-09
Applicant: Ford Global Technologies, LLC
Inventor： Frank Korpics , Dean Pennala , Devesh Upadhyay , Hao Wu
CPC classification number: B01D53/9495 , B01D53/9431 , F01N3/2066 , F01N9/00 , F01N11/00 , F01N2560/026 , F01N2610/02 , F01N2900/1402 , F01N2900/1616 , F01N2900/1621 , Y02T10/24 , Y02T10/47
Abstract: Systems and methods for detecting ammonia slip in an exhaust system based upon transient NOx sensor responses are described. In one example method, an exhaust system allocates tailpipe NOx sensor output to NOx and NH3 levels responsive to the transient sensors using a segment length method that processes the transient signals based on the total segment lengths calculated within a window. A ratio of segment lengths relative to a threshold is determined for a measured and expected NOx rate of change downstream of an SCR that is further used to determine a probability of NOx and NH3 based on the measured sensor activities, and a controller is included to adjust one or more parameters based on the allocation and changes of sensor output.
Abstract translation: 描述了基于瞬态NOx传感器响应来检测排气系统中氨滑移的系统和方法。 在一个示例性方法中，排气系统使用使用基于在窗口内计算的总段长度来处理瞬态信号的段长度方法来响应于瞬态传感器而将尾管NOx传感器输出分配给NO x和NH 3水平。 确定段长度相对于阈值的比率，用于SCR的下游的测量和预期的NOx变化率，其进一步用于基于测量的传感器活动来确定NOx和NH 3的概率，并且包括控制器以调整 基于传感器输出的分配和变化的一个或多个参数。
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公开(公告)号：US20240320505A1
公开(公告)日：2024-09-26
申请号：US18188024
申请日：2023-03-22
Applicant: Ford Global Technologies, LLC
Inventor： Kaushik Balakrishnan , Neeloy Chakraborty , Devesh Upadhyay
IPC: G06N3/092
CPC classification number: G06N3/092
Abstract: A computer that includes a processor and a memory, the memory including instructions executable by the processor to train an agent neural network to input a first state and output a first action, input the first action to an environment and determine a second state and a reward. Koopman model neural network can be trained based on the first state, the first action and the second state to determine a fake state. The agent neural network can be re-trained and the Koopman model neural network can be re-trained based on reinforcement learning including the first state, the first action, the second state, the fake state, and the reward.
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Patent Agency Ranking
公开(公告)号：US11977715B2
公开(公告)日：2024-05-07
申请号：US17171273
申请日：2021-02-09
Applicant: Ford Global Technologies, LLC
Inventor： Fling Finn Tseng , Johannes Geir Kristinsson , Daryl Martin , Bhagyashri Satyabodha Katti , Himanshu Verma , Shiqi Qiu , Jonathan Niemi , Devesh Upadhyay
IPC: G06F3/04842 , B60K35/00 , G06F3/04817 , B60K35/10 , B60K35/29 , B60K35/65
CPC classification number: G06F3/04817 , B60K35/00 , G06F3/04842 , B60K35/10 , B60K35/29 , B60K35/654 , B60K2370/119 , B60K2370/186
Abstract: An identifier for first set of display content on a vehicle display is input to a statistical model that outputs a plurality of probabilities that a user input will select each of a plurality of second set of display contents for display after the first set of display content is displayed. A first probability is identified for a predicted set of display content that is a highest probability in the plurality of probabilities. The plurality of probabilities are provided to at least one of an optimization model and a neural network upon determining an accuracy of the statistical model is below a threshold. Upon receiving, from the at least one of the optimization model and the neural network, a second probability for the predicted set of display content, the display content is selected based on the first and second probabilities. The vehicle display is updated based on the selected set of display content.
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公开(公告)号：US20230139013A1
公开(公告)日：2023-05-04
申请号：US17518623
申请日：2021-11-04
Applicant: Ford Global Technologies, LLC
Inventor： Kaushik Balakrishnan , Praveen Narayanan , Justin Miller , Devesh Upadhyay
Abstract: An image including a vehicle seat and a seatbelt webbing for the vehicle seat is obtained. The image is input to a neural network trained to, upon determining a presence of an occupant in the vehicle seat, output a physical state of the occupant and a seatbelt webbing state. Respective classifications for the physical state and the seatbelt webbing state are determined. The classifications are one of preferred or nonpreferred. A vehicle component is actuated based on the classification for at least one of the physical state of the occupant or the seatbelt webbing state being nonpreferred.
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公开(公告)号：US11423571B2
公开(公告)日：2022-08-23
申请号：US17097737
申请日：2020-11-13
Applicant: Ford Global Technologies, LLC
Inventor： Iman Soltani Bozchalooi , Alireza Rahimpour , Devesh Upadhyay
Abstract: A method includes detecting, for each of a plurality of images, a plurality of key points, where each of the plurality of images represents an object of an assembly system. The method includes generating, for each of the plurality of images, a correspondence between the plurality of key points, and generating, for each of the plurality of images, a reference region based on the correspondence between the plurality of key points. The method includes identifying, for each of the plurality of images, a reference key point among the plurality of key points based on the reference region, and determining a pose of the object based on the reference key point of each of the plurality of images and a reference pose of the object.
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公开(公告)号：US20220137634A1
公开(公告)日：2022-05-05
申请号：US17083469
申请日：2020-10-29
Applicant: Ford Global Technologies, LLC
Inventor： Iman Soltani Bozchalooi , Francois Charette , Dimitar Petrov Filev , Ryan Burke , Devesh Upadhyay
Abstract: A computer, including a processor and a memory, the memory including instructions to be executed by the processor to train a neural network included in a memory augmented neural network based on one or more images and corresponding ground truth in a training dataset by transforming the one or more images to generate a plurality of one-hundred or more variations of the one or more images including variations in the ground truth and process the variations of the one or more images and store feature points corresponding to each variation of the one or more images in memory associated with the memory augmented neural network. The instructions can include further instructions to process an image acquired by a vehicle sensor with the memory augmented neural network, including comparing a feature variance set for the image acquired by the vehicle sensor to the stored processing parameters for each variation of the one or more images, to obtain an output result.
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公开(公告)号：US20210397198A1
公开(公告)日：2021-12-23
申请号：US16904653
申请日：2020-06-18
Applicant: Ford Global Technologies, LLC
Inventor： Iman Soltani Bozchalooi , Francois Charette , Praveen Narayanan , Ryan Burke , Devesh Upadhyay , Dimitar Petrov Filev
Abstract: A computer includes a processor and a memory storing instructions executable by the processor to receive an image including a physical landmark, output a plurality of synthetic images, wherein each synthetic image is generated by simulating at least one ambient feature in the received image, generate respective feature vectors for each of the plurality of synthetic images, and actuate one or more vehicle components upon identifying the physical landmark in a second received image based on a similarity measure between the feature vectors of the synthetic images and a feature vector of the second received image, the similarity measure being one of a probability distribution difference or a statistical distance.
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