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Previous predictions from 1D analyses provided a less-than-desirable first-test success rate, closer to 70% on average. CFD has jumped that average rate up to 90%.

Assessing a vehicle’s cooling system performance

Off-highway OEMs historically have utilized simple 1-Dimensional analyses (either themselves or through their cooling system suppliers) to predict the cooling performance of each vehicle’s engine system. These analyses produce a low accuracy rate, which often results in late design changes leading to delays in the overall project.

To improve this situation, manufacturers have a tool at their disposal in computational fluid dynamics (CFD). Using inputs of temperatures, flows, restrictions, heat transfer ability of coolers, and 3-Dimensional models of vehicle architecture, a 3D prediction of the cooling performance can be achieved. The 3D prediction results in an overall systems design with a higher success rate during validation.

JLG has been routinely using CFD software tools from industry-leading suppliers for more than five years, when developing new engine bay installations. The introduction of so many new engine variants, including hybrid drives and global emissions legislation variants, has driven the need to get it right the first time while managing even more variables.

The example described here is an extract from the analysis performed on a JLG 1500AJP Ultra Boom, launched in 2016.

CFD reveals design inefficiencies

There are often multiple coolers that make up a system. Each of these coolers must work together to provide the required level of performance for each part of the system. By making sure that each cooler is balanced with the proper airflow, preheat temperatures and more, the desired performance of the system will be achieved.

By utilizing CFD in the early stages of the design process, engineers can iterate in a soft environment to achieve the desired performance. By doing so, the team can avoid changes in the validation portion of the design cycle which are common when using 1D analyses.

Once an initial design of the cooling system has been created, it is time to use the CFD tool to analyze the efficiency of each individual cooler. In this specific case, the internal temperatures and cooler flows (constants, liquids and air) versus the heat exchanger efficiencies (constants) are mapped as a heat rejection from the system to the vehicle’s environment based on the external cooler flows (air), which the CFD tool is simulating.

CFD revealed the following about the initial design of the cooling system:

• Engine liquid coolant was being cooled to 110% of the requirement

• Engine charge air was being cooled to only 75% of the requirement

• Vehicle hydraulics were being cooled to 109% of the requirement.

While two of the systems were performing optimally, the engine charge air cooler was below the requirement. Based on the design, it was determined that the engine liquid cooler needed to be made smaller while the engine charge air cooler needed to be larger. Even though the hydraulic oil cooler was performing above the requirement, the size did not need to be changed. However, its location in front of the other two coolers was changed to balance the airflow correctly.

Once each of the changes was finalized, a second run-through using the CFD tool was completed. It resulted in the following:

• Engine liquid coolant was being cooled to 101% of the requirement

• Engine charge air was being cooled to 109% of the requirement

• Vehicle hydraulics were being cooled to 110% of the requirement.

Each of the cooling systems were shown to be sufficient and able to perform to the requirements of the vehicle’s overall system. With this information from the simulation, the project continued. Later, an actual vehicle validation confirmed the positive results from this simulation.

Future challenges and opportunities

CFD is not a replacement for the physical testing of applications. In the access industry, it is certainly an improvement to the original 1D analyses that were being provided. Previous predictions provided a less-than-desirable first-test success rate, closer to 70% on average. Typically the errors occurred in overall airflow, air inlet and outlet orifices and the split between hydraulic, engine coolant and transmission oil in the cooler stack. CFD has jumped that average success rate up to 90%. Despite this drastic increase in success, vehicle validation needs to be completed to confirm the results of the CFD simulation and analysis and all aspects of a vehicle’s cooling system.

At JLG, the use of CFD to ensure optimized cooling performance will continue to evolve, with Stage V engine legislation introducing new components with distinct thermal requirements, such as diesel particulate filters (DPFs). Also evolving are the varieties of power systems, such as hybrid drives and their associated components, such as clutches, electronic controllers and charging systems.

In conjunction with the continued development in power systems are related analyses such as noise and vibration, where the analysis of energy, airflows and pressures can be simulated and analyzed. In the future, new manufacturing processes, such as additive manufacturing and 3D printing, provide new opportunities to optimize components’ forms for fluid flow characteristics.

Brian Barkley, Senior Chief Engineer, JLG Industries, Inc., wrote this article for Truck & Off-Highway Engineering.

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