Design Space Exploration zur multikriteriellen Optimierung elektrischer Sportwagenantriebsstränge: Variation von Topologie und Komponenteneigenschaften zur Steigerung von Fahrleistungen und Tank-to-Wheel Wirkungsgrad

Vaillant, Moritz

doi:10.5445/ksp/1000050618

Cited by 5 publications

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Implementation and Analyses of an Eco-Driving Algorithm for Different Battery Electric Powertrain Topologies Based on a Split Loss Integration Approach

et al. 2022

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Eco-driving algorithms optimize the speed profile to reduce the energy consumption of a vehicle. This paper presents an eco-driving algorithm for battery electric powertrains that applies a split loss integration approach to incorporate the component losses. The algorithm consistently uses loss models to overcome the drawbacks of efficiency maps, which cannot represent no-load losses at zero torque. The use of loss models is crucial since the optimal solution includes gliding, during which there are no-load losses. An analysis shows, that state-of-the-art nonlinear programming algorithms cannot represent these no-load losses at zero torque with a small modeling error. To effectively compute the powertrain losses with only a small error in comparison to the measurement data, we introduce a tailored combination of nonlinear inequality constraints that interleave two polynomial fits. This approach can properly represent reality. We parameterize the algorithm and validate the vehicle model used with real-world measurement data. Furthermore, we investigate the influence of the proposed interleaved fits by comparing them to a single continuous high-order polynomial fit and to the state of the art. The algorithm is published open source.

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Implementation and Analyses of an Eco-Driving Algorithm for Different Battery Electric Powertrain Topologies Based on a Split Loss Integration Approach

et al. 2022

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An Iterative Method Based on the Marginalized Particle Filter for Nonlinear B-Spline Data Approximation and Trajectory Optimization

et al. 2019

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The B-spline function representation is commonly used for data approximation and trajectory definition, but filter-based methods for NWLS approximation are restricted to a bounded definition range. We present an algorithm termed NRBA for an iterative NWLS approximation of an unbounded set of data points by a B-spline function. NRBA is based on a MPF, in which a KF solves the linear subproblem optimally while a PF deals with nonlinear approximation goals. NRBA can adjust the bounded definition range of the approximating B-spline function during run-time such that, regardless of the initially chosen definition range, all data points can be processed. In numerical experiments, NRBA achieves approximation results close to those of the Levenberg–Marquardt algorithm. An NWLS approximation problem is a nonlinear optimization problem. The direct trajectory optimization approach also leads to a nonlinear problem. The computational effort of most solution methods grows exponentially with the trajectory length. We demonstrate how NRBA can be applied for a multiobjective trajectory optimization for a BEV in order to determine an energy-efficient velocity trajectory. With NRBA, the effort increases only linearly with the processed data points and the trajectory length.

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Physics-Based and Data-Enhanced Model for Electric Drive Sizing during System Design of Electrified Powertrains

et al. 2021

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In multi-drive electrified powertrains, the control strategy strongly influences the component load collectives. Due to this interdependency, the component sizing becomes a difficult task. This paper comprehensively analyses different electric drive system sizing methods for multi-drive systems in the literature. Based on this analysis, a new data-enhanced sizing approach is proposed. While the characteristic is depicted with a physics-based polynomial model, a data-enhanced limiting function ensures the parameter variation stays within a physically feasible range. Its beneficial value is demonstrated by applying the new model to a powertrain system optimization. The new approach enables a detailed investigation of the correlations between the characteristic of electric drive systems and the overall vehicle energy consumption for varying topologies. The application results demonstrate the accuracy and benefit of the proposed model.

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Design Space Exploration zur multikriteriellen Optimierung elektrischer Sportwagenantriebsstränge: Variation von Topologie und Komponenteneigenschaften zur Steigerung von Fahrleistungen und Tank-to-Wheel Wirkungsgrad

Cited by 5 publications

References 0 publications

Implementation and Analyses of an Eco-Driving Algorithm for Different Battery Electric Powertrain Topologies Based on a Split Loss Integration Approach

Implementation and Analyses of an Eco-Driving Algorithm for Different Battery Electric Powertrain Topologies Based on a Split Loss Integration Approach

An Iterative Method Based on the Marginalized Particle Filter for Nonlinear B-Spline Data Approximation and Trajectory Optimization

Physics-Based and Data-Enhanced Model for Electric Drive Sizing during System Design of Electrified Powertrains

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