Simulation-Based Optimization of a Series Hydraulic Hybrid Vehicle

Abstract

"The brick walls are there for a reason. (...) [They] are there to give us a chance to show how badly we want something. Randy Pausch AbstractHybrid transmissions are characterized by their utilization of more than one form of energy storage. They have the potential to help reduce overall fuel consumption and vehicle emissions by providing the possibility of brake energy recuperation and prime mover operation management. Electric hybrids and electric vehicle drives are nowadays ubiquitous, and mechanical energy storage in flywheel has been investigated in the past. The use of fluid power technology with a combustion engine has also been investigated since the late 1970s, and is frequently revisited.Hydraulic hybridization is especially attractive for heavy vehicles with frequent braking and acceleration which benefit most from fluid power components' high power density, typically busses, delivery or refuse vehicles, and vehicles with existing hydraulic circuits and transmissions, such as forest and construction machinery, but have been considered for smaller vehicles as well.Due to the characteristic discharge profile of hydraulic energy storage, special attention needs to be paid to control aspects in the design process to guarantee drivability of the vehicle. In this respect, simulation models can be of use in early design process stages for cheaper and faster evaluation of concepts and designs than physical experiments and prototyping, and to generate better understanding of the system studied. Engineering optimization aids in the systematic exploration of a given design space, to determine limits and potentials, evaluate trade-offs and potentially find unexpected solutions. In the optimization of a hydraulic hybrid transmission, the integration of component and controller design is of importance, and different strategies (sequential, iterative, bi-level and simultaneous approaches) are conceivable, with varying consequences for the implementation.This thesis establishes a simulation-based optimization framework for a hydraulic hybrid transmission with series architecture. Component and control parameter optimization are addressed simultaneously, using a rule-based supervisory control strategy. The forward-facing dynamic simulation model at the centre of the framework is built in Hopsan, a multi-disciplinary open-source tool developed at Linköping University. The optimization is set up and conducted for an example application of an on-road light-duty truck over standard drive i cycles. Both results from these experiments as well as the framework itself are studied and evaluated. Relevant design aspects, such as explicit design relations to be considered and performance requirements for more robust design, are identified and addressed, and the optimization problem is analysed with regard to algorithm performance and problem formulation. The final result is an optimization framework that can be adjusted for further in-depth studies, for example through the inclusion of additional components or optimization obj...

Robustness and performance evaluations for simulation-based control and component parameter optimization for a series hydraulic hybrid vehicle

“…All results presented here were obtained for optimization over the UDDS. The consideration of alternative and additional driving schedules affects the designs (Baer 2018) and may impact the optimization algorithm performance as well. Beyond the scope of the model in this study, additional design modifications can be of interest in a comparative design optimization process as well.…”

“…The forward-facing SHHV transmission model (Figure 2, see Baer [2018] for more details) consists of a diesel engine driving an hydraulic pump, an hydraulic accumulator without designated inlet control valve, and an hydraulic pump/motor connected directly to the vehicle's final drive. The vehicle load is modelled considering inertial mass acceleration, road load from friction and aerodynamic drag.…”

Energy Management Based on Neural Networks for a Hydraulic Hybrid Wheel Loader

“…However, it is expected that the methods could be adapted and/or combined to generate suitable EMSs for construction machines. This approach seems to be true, as argued in [3][4][5][6][7][8][9].…”

On Machine Learning-Based Control for Energy Management in Construction Machines

“…Hybrid machines, on the other hand, are characterised by two or more energy storage devices. Hybridisation aims to reduce energy consumption and/or reduce emissions through the combined use of several sources of energy to meet the power demanded from consumers [1]. Typically, one of the energy sources can perform energy recuperation.…”