Powerbike - Model-based optimal control for cycling

Powerbike - 基于模型的骑行优化控制

• 批准号: 247721022
• 负责人: Professor Dr. Dietmar Saupe
• 金额: --
• 依托单位: Arbeitsgruppe Multimedia Signalverarbeitung
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2013
• 资助国家: 德国
• 起止时间: 2012-12-31 至 2017-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/247721022?language=en
• 关键词: Powerbike; Model; based; optimal; control

Our project connects Computer Science in Sport (Sportinformatik) with mathematical modeling, numerics, and sport science. We contribute to modeling and prediction for cycling as an example of endurance sports by- designing, calibrating, and validating mathematical physiological models that provide the means to analyze and predict cycling performance, and by- deriving methods to compute optimal pacing strategies for cycling time trials based on these models.The modeling for performance analysis in road cycling is twofold. Firstly, the mechanical aspects of cycling include the physics of the bicycle propulsion. Secondly, a physiological model of the individual athlete is required which should provide available power and energy resources at any point in time. Such a model is much more difficult to achieve than the physical one. It is impossible to accurately simulate all relevant physiological aspects because of the vast complexity of the human organism encompassing numerous subsystems with scales down to the cellular level. Thus, a compromise between the level-of-detail and the necessary abstraction of the model must be made. For this task we will use semi-physical system modeling. Basic elements of the structure of the system will be motivated by current state-of-the-art physiological models while some of the internal system details will be left for the system identification. Moreover, the parameters of such physiological models need to be estimated for individual athletes. This calibration is difficult and may render a possibly accurate but too complex model useless in practice. System identification and parameter estimation can be based best on input-output pairs. Input is a load profile in a suitably chosen ergometer test. Output is respiratory gas exchange, heart rate or variability, and lactate blood level. With models on hand we can compute minimum-time pacing strategies by solving certain mathematical optimal control problems. The physical and physiological models provide a system of constrained differential equations with a control which is the pacing strategy. Recently improved numerical algorithms designed to solve general optimal control problems efficiently are available, partly as well developed open-source software. However, the specific problem still contains some features that require additional methods to guarantee reliable convergence.Our proposed work includes an evaluation. Firstly, testing protocols must be developed to determine the parameters for physiological models to evaluate the validity and accuracy of these models. Secondly, optimal pacing strategies will be tested first on our cycling simulator, and then also in the field which requires a gps-enabled feedback device that provides the cyclist with the information about the optimal pacing in real-time. Ideally, the device should update online the optimal pacing strategy while on the road.

我们的项目将体育计算机科学（SportInformatik）与数学建模，数字和运动科学联系起来。我们为骑自行车的建模和预测做出了贡献，作为耐力运动，设计，校准和验证数学生理模型，这些模型提供了分析和预测循环性能的手段，以及通过这些模型计算循环时间试验的最佳加速策略的方法。首先，骑自行车的机械方面包括自行车推进的物理。其次，需要单个运动员的生理模型，该模型应在任何时间点提供可用的功率和能源。这样的模型比物理模型要难得多。由于人类有机体的巨大复杂性，涵盖了许多子系统，因此无法准确模拟所有相关的生理方面。因此，必须在模型的范围和必要的抽象之间妥协。对于此任务，我们将使用半物理系统建模。系统结构的基本要素将由当前的最新生理模型激励，而某些内部系统详细信息将用于系统识别。此外，需要估算为个别运动员的这种生理模型的参数。这种校准很困难，并且可能在实践中变得无用，但可能会变得准确但过于复杂。系统标识和参数估计可以最佳基于输入输出对。输入是适当选择的测量计测试中的负载曲线。输出是呼吸道气体交换，心率或变异性以及乳酸血液水平。借助现场模型，我们可以通过解决某些数学最佳控制问题来计算最低时间的起搏策略。物理和生理模型提供了一个受约束微分方程的系统，并具有节奏策略的控制。最近改进了旨在有效解决一般最佳控制问题的数值算法，部分是开发的开源软件。但是，特定问题仍然包含一些需要其他方法来保证可靠收敛的功能。我们的拟议工作包括评估。首先，必须制定测试协议以确定生理模型的参数，以评估这些模型的有效性和准确性。其次，最佳起搏策略将首先在我们的循环模拟器上进行测试，然后在现场进行，该策略需要启用GPS的反馈设备，该反馈设备为骑自行车者提供了有关实时最佳起搏的信息。理想情况下，设备应在路上在线更新最佳的节奏策略。

项目成果

Adaptive feedback system for optimal pacing strategies in road cycling

• DOI: 10.1007/s12283-019-0294-5
• 发表时间: 2019-03-01
• 期刊: SPORTS ENGINEERING
• 影响因子: 1.7
• 作者: Wolf, Stefan;Biral, Francesco;Saupe, Dietmar
• 通讯作者: Saupe, Dietmar

How to Stay Ahead of the Pack: Optimal Road Cycling Strategies for two Cooperating Riders

如何保持领先地位：两名合作骑手的最佳公路骑行策略

• DOI: 10.1515/ijcss-2017-0008
• 发表时间: 2017
• 期刊: International Journal of Computer Science in Sport

Modeling V?O2 and V?CO2 with Hammerstein-Wiener Models

使用 Hammerstein-Wiener 模型模拟 V?O2 和 V?CO2

• DOI: 10.5220/0006086501340140
• 发表时间: 2016
• 作者: Artiga Gonzalez;Bertschinger
• 通讯作者: Bertschinger

How to Accurately Determine the Position on a Known Course in Road Cycling

如何准确确定公路自行车已知路线上的位置

• DOI: 10.1007/978-3-319-67846-7_11
• 发表时间: 2017
• 作者: Dobiasch;Artiga Gonzalez
• 通讯作者: Artiga Gonzalez

Road Cycling Climbs Made Speedier by Personalized Pacing Strategies

• DOI: 10.5220/0006080001090114
• 发表时间: 2016-01-01
• 期刊: ICSPORTS: PROCEEDINGS OF THE 4TH INTERNATIONAL CONGRESS ON SPORT SCIENCES RESEARCH AND TECHNOLOGY SUPPORT
• 作者: Wolf, Stefan;Bertschinger, Raphael;Saupe, Dietmar
• 通讯作者: Saupe, Dietmar