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The usage and control of combustion engines has a significant effect in the fuel consumption and controllability of mobile work machines. In general, the best efficiency region of engine is at high partial loads. In this area, the challenge is the reduced reaction speed of engine. In this paper, we present an approach to gain high fuel efficiency and good drivability by reducing the rotational speed of the engine. This is possible due the fact that hydrostatic power transmission provides variable gear ratio between the engine and the actuators. At reduced rotational speed, engine operates with higher partial loads and improved fuel efficiency for a given required power. The experimental drive cycle tests are presented and show over 25% reduction in fuel consumption compared to conventional control where engine rotational speed is kept constant.

This paper presents an optimal controller for fuel efficiency of a hydraulic mobile machine with hydrostatic drive (HSD). The solution is validated using a semi-empirical simulated research platform. The drive transmission of the machine includes one variable displacement hydraulic pump and four two-speed hub motors. There is no energy storage installed. Thus, the structure of the HSD and presented improvements in fuel economy are comparable to traditional machines. The optimal controller is compared to a baseline controller that intuitively keeps the components at their high efficiency regions. In simulated hill tests, fuel economy was improved by up to 25.9 % depending on the slope of the hill and velocity reference.

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In this article, we devise a nonlinear model predictive control framework for the energy management of nonhybrid hydrostatic drive transmissions. The controller determines the optimal control commands of the actuators by minimising a cost function over a receding horizon. With our approach, the velocity-tracking error is minimised while keeping the fuel economy of the system high. The hydrostatic drive transmission system studied in this article is a typical commercial work machine, that is, there is no energy storage or alternative power source in the system (a nonhybrid hydrostatic drive transmission). We evaluate success with a validated simulation model of the hydrostatic drive transmission of a municipal tractor. In our experiments, a detailed system model is used both in the system simulation and in the prediction phase of the nonlinear model predictive control. The use of a detailed model in the nonlinear model predictive control framework places our design as a benchmark for controlling nonhybrid hydrostatic drive transmissions, when compared to solutions using simplified models or computationally less intensive control methods as in earlier work by the authors. Our nonlinear model predictive control approach enables numerically robust optimisation convergence with the utilised complex nonlinear model. Above all, this is accomplished with stabilising terminal constraints and distinctive terminal cost, both based on an optimal steady-state solution. In addition, a simple method to generate initial guesses for optimisation is introduced. When compared with the performance of a controller based on quasi-static models, our results show notable improvement in velocity tracking while maintaining high fuel economy. Furthermore, our experiments demonstrate that framing energy management as a nonlinear model predictive control provides a flexible and rigorous framework for fast velocity tracking and high energy efficiency. We also compare the results with those of an industrial baseline controller.