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<p>The aim of this work is the consumption-optimized synthesis of an electro-mechanical power-split hybrid drive for a&#xa0;reference vehicle for local rail passenger transport on a&#xa0;given track with a&#xa0;given speed profile. First, a&#xa0;method for the optimization of the operating strategy (energy management) is developed using dynamic programming. This methodology is then applied to several variations of the drivetrain (available operating modes, transmission ratios, drive power of electric machines) to deduce a&#xa0;drivetrain configuration along with an operating strategy for the reference application which exhibits a&#xa0;global minimum regarding the fuel consumption. Results show that the battery-electric and power-split modes are the most efficient operating modes and that the drive power of the electric machines has the most significant impact on fuel consumption. Overall, the findings indicate that a&#xa0;fuel saving of up to 37.5% compared to a&#xa0;conventional diesel-mechanical reference drive operated on the same reference route can be realized with the presented optimization approach.</p>

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Optimization of power-split hybrid drives and of their operating strategy using dynamic programming

  • 期刊论文

  • 发表日期：

    2025年2月20日

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  • Hendrik Hoffmann

摘要

The aim of this work is the consumption-optimized synthesis of an electro-mechanical power-split hybrid drive for a reference vehicle for local rail passenger transport on a given track with a given speed profile. First, a method for the optimization of the operating strategy (energy management) is developed using dynamic programming. This methodology is then applied to several variations of the drivetrain (available operating modes, transmission ratios, drive power of electric machines) to deduce a drivetrain configuration along with an operating strategy for the reference application which exhibits a global minimum regarding the fuel consumption. Results show that the battery-electric and power-split modes are the most efficient operating modes and that the drive power of the electric machines has the most significant impact on fuel consumption. Overall, the findings indicate that a fuel saving of up to 37.5% compared to a conventional diesel-mechanical reference drive operated on the same reference route can be realized with the presented optimization approach.