Using optimal control in concept evaluation and system optimization of diesel-electric hybrid construction machines

A method that enables evaluation on new construction machine concepts, such as diesel-electric hybrid construction machines, is presented. The method is unbiased from control engineer experience, development time and tuning of algorithms for each concept. The impact of inconsistent operator behavior and deviations in complete machine tests are also minimized. The method is based on dynamic programming and finds the global optimum in regards to fuel efficiency [ton/l] at any given productivity [ton/h] for each concept to enable an objective comparison between the concepts. In the method, a system optimization is included that ensures that each concept is evaluated with the optimal setup of component sizes, within the boundary conditions set by machine performance requirements. Two different diesel-electric hybrid machine concepts, including both drive line and working hydraulics, are investigated; parallel hybrid and series hybrid. Both are compared to the conventional machine. The main focus is on evaluating concepts that are so different that control algorithms and machine models cannot be based on a conventional machine. The wheel loader is used as an example due to the complex nature of the system, with a driveline and working hydraulics that have to work together throughout the work cycle. The interaction between the gravel pile and bucket is also considered, in order to simulate, and optimize, the complete work cycle. A wheel loader in a bucket application, performing a “short loading cycle” as part of a production chain is used as an example. This is a common application for larger wheel loaders, hence an important application to optimize for. The main result is that the method and algorithms presented in this paper works. Additional results show that a parallel hybrid wheel loader has approximately 5% higher fuel efficiency and a series hybrid approximately 23% higher comparing to the conventional machine, in the investigated application. The system optimization shows that for example a correctly sized genset, internal combustion engine and electrical machine, in a series hybrid can improve the fuel efficiency approximately 6%, in this application. The comparison is between the optimal downsized genset and a genset in the same size as the internal combustion engine in a conventional machine. The method presented can also be used in other complex machines, such as; agriculture, forestry and road vehicles.