Controlling the longitudinal movement of heavy-duty vehicles based on optimal control can be a cost-efficient way of reducing their fuel consumption. Such controllers today mainly exist for highway driving, in which the velocity is allowed to deviate from a constant set-speed. For vehicles with varying velocity demands, for instance vehicles in distribution and mining applications, such controllers do not exist to the same extent. This paper describes an implementation of, and experiments with, an optimal controller in a real heavy-duty vehicle. The velocity profile of the driving cycle varies due to curvature and varying legal speed limits. These limitations are used together with road slope, actuator limitations, and driveability considerations as constraints in the optimal control problem. The problem is solved offline as a mixed integer quadratic program, which generates trajectories for the velocity and for freewheeling. These are used as reference for the existing cruise control functions in experiments in a Scania truck. Results in terms of fuel consumption and trip time are compared with a benchmark controller that mainly follows a fixed fraction of the maximum possible velocity. Solving the optimal control problem results in 18% reduction of the fuel consumption and 1% reduction of the trip time. Experiments with fuel measurements results in 16% reduction of the fuel consumption and 1% reduction of the trip time.

基于最佳控制来控制重型车辆的纵向运动可能是降低其燃油消耗的一种经济高效的方式。如今，这种控制器主要用于高速公路驾驶，在这种情况下，速度可以偏离恒定的设定速度。对于具有不同速度要求的车辆，例如配电和采矿应用中的车辆，此类控制器的存在程度不同。本文介绍了一种在重型汽车中实现最佳控制器的实验。行驶周期的速度曲线会因曲率和合法的速度限制而变化。这些限制与道路坡度，执行器限制和可驾驶性考虑一起用作最佳控制问题的限制。通过混合整数二次程序离线解决该问题，该程序生成速度和惯性滑行的轨迹。这些用作Scania卡车实验中现有巡航控制功能的参考。将燃油消耗和行程时间方面的结果与基准控制器进行比较，该基准控制器主要遵循最大可能速度的固定分数。解决最佳控制问题将使燃油消耗减少18％，行程时间减少1％。进行燃油测量的实验使燃油消耗减少了16％，行程时间减少了1％。将燃油消耗和行程时间方面的结果与基准控制器进行比较，该基准控制器主要遵循最大可能速度的固定分数。解决最佳控制问题将使燃油消耗减少18％，行程时间减少1％。进行燃油测量的实验使燃油消耗减少了16％，行程时间减少了1％。将燃油消耗和行程时间方面的结果与基准控制器进行比较，该基准控制器主要遵循最大可能速度的固定分数。解决最佳控制问题将使燃油消耗减少18％，行程时间减少1％。进行燃油测量的实验使燃油消耗减少了16％，行程时间减少了1％。