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Wheel loader subsystems are multi-domain in nature, including controls, mechanisms, hydraulics, and thermal. This paper describes the process of developing a multi-domain simulation of a wheel loader. Working hydraulics, kinematics of the working tool, driveline, engine, and cooling system are modeled in LMS Imagine.Lab Amesim. Contacts between boom/bucket and bucket/ground are defined to constrain the movement of the bucket and boom. The wheel loader has four heat exchangers: charge air cooler, radiator, transmission oil cooler, and hydraulic oil cooler. Heat rejection from engine, energy losses from driveline, and hydraulic subsystem are inputs to the heat exchangers. 3D CFD modeling was done to calibrate airflows through heat exchangers in LMS Amesim. CFD modeling was done in ANSYS FLUENT® using a standard k - ε model with detailed fan and underhood geometry.

Fuel usage negatively impacts the environment and is a significant portion of operational costs of moving freight globally. Reducing fuel consumption is key to lessening environmental impacts and maximizing freight efficiency, thereby increasing the profit margin of logistic operators. In this paper, fuel economy improvements of a cab-over style 49T heavy duty Foton truck powered by a Cummins 12-liter engine are studied and systematically applied for the China market. Most fuel efficiency improvements are found within the vehicle design when compared to opportunities available at the engine level. Vehicle design (improved aerodynamics), component selection/matching (low rolling resistance tires), and powertrain electronic features integration (shift schedule/electronic trim) offer the largest opportunities for lowering fuel consumption.

Understanding the complex and dynamic nature of wheel-loader's operation requires a detailed system model. This paper describes the development of a conventional wheel-loader's system model that can be used to evaluate the transient response. The model includes engine details such as a mean value engine model, which takes into account turbocharger dynamics and engine governor controller. This allows the model to predict realistic performance and fuel consumption over a drive cycle. The wheel-loader machine is modeled in LMS Amesim® and the engine governor controller is modeled in Matlab/SIMULINK®. In order to simplify the model, hydraulic loads from the boom / bucket mechanism, steering and cooling fan are modeled as hydraulic load inputs obtained from typical short V-drive cycle. Critical wheel-loader drive cycle inputs into the model have been obtained from testing and have been used to validate the system response and cycle fuel consumption.