The design of motorcycle engine cooling systems is often hampered by a trade-off
between computational efficiency and simulation accuracy, making optimized
design iterative and costly. A streamlined, coupled 1D–3D methodology, validated
across diverse engine configurations, is needed to address this challenge. This
study develops and validates an iterative simulation framework to efficiently
optimize cooling systems for various motorcycle engines. The 1D system model
defines the performance targets, while 3D CFD analysis enables detailed
component optimization (water jackets, radiator airflow); an iterative process
ensures the target fulfillment. The 1D–3D coupling analysis methodology is
applied to single-, two-, and four-cylinder engines. Results show that the
coolant flow velocity within the water jackets are sufficient to ensure
effective heat removal of engines and confirms the rational layout design of
water jackets. The radiator inlet coolant temperature for the original design of
those three engines cooling are 109°C, 107°C, 103°C, respectively. Optimizations
(fan shroud redesign, impeller width increase, airflow outlet redesign, air
guiding device, radiator shield, wind shielding area reduction, cover removal)
are made to increase the radiator airflow velocity by 34.92%, 12%, 7.5%,
respectively, and successfully reduces the radiator inlet temperatures below the
100°C target (from 109°C to 99°C, 107°C to 100°C, and 103.8°C to 99.2°C,
respectively), with results validated experimentally. The deviation between
simulation and experiments is below 7%, confirming the overall reliability and
accuracy of the simulation model. The study provides a validated, scalable
framework for optimizing motorcycle engine cooling systems, balancing accuracy
with efficiency. Its applicability to the cases presented suggests potential for
broader use in hybrid and electric powertrain thermal management.
