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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.

Traditionally, most charge air coolers (CACs) have been constructed using the Nocolok aluminum brazing process. The Nocolok process uses flux, some of which remains after the manufacturing process, and migrates through the intake tract to the engine during normal use. This migration and deposition on engine components can cause a variety of issues with engine operation. Currently the only alternative to Nocolok brazed CACs for engines sensitive to flux migration is vacuum brazing, which comes at a significant price increase. In the effort to reduce cost and increase efficiency, there is interest in whether a Nocolok brazed CAC with a reduced amount of flux residue can be successfully applied to flux-sensitive engines.

This paper describes the methodology used to select an application-based fan that has optimum operating characteristics in terms of cooling air flow rate, fan power, and noise. The selected fan is then evaluated for structural strength. To evaluate different fans, complete rail coach under-hood simulations were carried out using steady-state 3D computational fluid dynamics (CFD) approach. These simulations considered an actual, highly non-uniform flow field. For each fan option, fan power, air flow rate, and surface acoustic power was evaluated. Pressure profiles on the fan blades were studied to assess the effect of non-uniform downstream air passage designs. Surface acoustic power was calculated using broadband noise source (BNS) model in ANSYS Fluent®. Surface pressure profiles over fan blades imported from 3D CFD were used in finite element analysis (FEA) in ANSYS. Analyses were carried out for blade linear and non-linear properties.

Various 1D simulation tools (KULI & LMS Amesim) and 3D simulation tools (ANSYS FLUENT®) can be used to size and evaluate truck cooling system design. In this paper, ANSYS FLUENT is used to analyze and validate the design of medium duty truck cooling systems. LMS Amesim is used to verify the quality of heat exchanger input data. This paper discusses design and simulation of parent and derivative trucks. As a first step, the parent truck was modeled in FLUENT (using standard' k - ε model) with detailed fan and underhood geometry. The fan is modeled using Multiple Reference Frame (MRF) method. Detailed geometry of heat exchangers is skipped. The heat exchangers are represented by regular shape cell zones with porous medium and dual cell heat exchanger models to account for their contributions to the entire system in both flow and temperature distribution. Good agreement is observed between numerical and experimental engine out temperatures at different engine operating conditions.

Coolant filters have been used for nearly 50 years by heavy duty engine manufacturers but little has been published in the technical literature documenting their performance. In heavy duty cooling systems an extender is periodically added to the system to prevent the coolant from becoming corrosive and replenish additives that stop the build-up of deposits which reduce heat transfer. Not only is the coolant filter the most convenient and reliable method to deliver the extender to the cooling system, it also removes debris from the coolant which can cause deposits and wear, aggravate corrosion, and even plug heat exchangers. Additionally, the used coolant filter serves as a diagnostic trouble shooting tool. This paper concentrates on the value or importance of filtering debris from the coolant of heavy duty diesel engine cooling systems. Published literature is reviewed and recent data from lab testing is reported.

In the early years of antifreeze/coolants (1920s & 30s) glycerin saw some usage, but because of higher cost and weaker freeze point depression, it was not competitive with ethylene glycol. Glycerin is a by-product of the manufacture of biodiesel (fatty acid methyl esters) made by reacting natural vegetable or animal fats with methanol. Biodiesel fuel is becoming increasingly important and is expected to gain a large market share in the next several years. Regular diesel fuels blended with 2%, 5%, and 20% biodiesel are now commercially available. The large amount of glycerin generated from high volume usage of biodiesel fuel has resulted in this chemical becoming cost competitive with the glycols currently used in engine coolants. For this reason, and lower toxicity comparable to that of propylene glycol, glycerin deserves to be reconsidered as a base for antifreeze/coolant.

The thermal performance of an engine coolant system is efficient when the engine head temperature is maintained within its optimum working range. For this, it is desired that air should not be entrapped in the coolant system which can lead to localized hot spots at critical locations. However, it is difficult to eliminate the trapped air pockets completely. So, the target is to minimize the entrapped air as much as possible during the coolant filling and deaeration processes, especially in major components such as the radiator, engine head, pump etc. The filling processes and duration are typically optimized in an engine test stand along with design changes for augmenting the coolant filling efficiency. However, it is expensive and time consuming to identify air entrapped locations in tests, decide on the filling strategy and make the design changes in the piping accordingly.