Introduction

Abstract

Nonlinear system behavior of hybrid electric vehicle powertrains demands advanced methodologies in modeling and control in order to achieve optimal results by energy and battery management systems of such powertrains. This book describes the main problems in the real-time control of parallel hybrid electric powertrains in non-road applications, which work in continuous high dynamic operation. In order to maximize the energetic efficiency of such powertrains, the operation point of the engine must be kept in the optimal region. In terms of driveability, the optimal regions are mostly in regions with lower dynamics, which leads to engine stalling at high load peaks. This must be prevented by the controller in any case. For this purpose, the book addresses an energy management control structure, which considers all constraints of the physical powertrain and uses novel methodologies for the prediction of future load requirements to optimize controller output in terms of an entire work cycle of a non-road vehicle. The load prediction includes a methodology for short term loads as well as for an entire load cycle by means of cycle detection. This way, energy efficiency can be maximized, which simultaneously results in a reduction of fuel consumption and exhaust emissions. One significant information required by the energy management system is the battery’s state of charge, which is not measurable on-line. This requires an accurate state of charge estimation, which is based on a dynamic battery model. A novel methodology is introduced for the nonlinear battery modeling that also considers the design of experiments of the measurements to identify model parameters with minimum variance. The reader of the book gets a deep insight into the necessary topics to be considered in designing an energy and battery management system for non-road vehicles and learns that only a combination of the management systems can significantly increase the performance of a controller.