Road load data (RLD) has evolved significantly and is now a proven method for evaluating the roadworthiness of vehicles across all surface conditions, whether the objective is passenger comfort or overall vehicle durability. RLD encompasses a comprehensive set of technical inputs that a vehicle experiences during real-world operation across representative road profiles and load cases. The broader and more representative the range of inputs considered, the more robust and reliable the resulting outcomes—ultimately supporting durability assessment, structural design validation, fatigue life prediction, and NVH development. In modern vehicle programs, including ICE, hybrid, and electric platforms, accurate RLD enables teams to shorten development cycles, minimize over-design, and ensure reliability under actual customer usage conditions.
The broad scope of RLD is:
- To quantify real-world loading conditions at vehicle subsystems and components
- To support durability and fatigue life calculations
- To generate mission profiles for accelerated testing
- To validate CAE models and test assumptions
- To correlate NVH complaints with road-induced excitation
- To design proving ground and lab test schedules that represent customer usage
Typical Load data acquisition depiction
A typical RLD is an entire program in itself combining a variety of sensors, instrumentation, data processing tools and finally a systematic execution approach. Following item heads cover the most essential parameters for such a testing
- Wheel forces and moments (using Wheel Force Transducers – WFTs)
- Suspension loads (strain gauges on control arms, links, springs)
- Chassis accelerations (at body, subframe, and component interfaces)
- Steering, brake, and drivetrain signals
- Vehicle operating parameters (speed, gear, torque, steering angle)
RLD process worksheet and data outputs
In specific case, other influencing data may be considered to complete the RLD model. To obtain meaningful and qualified data, the road types and loads are selected carefully based on the vehicle / customer usage:
- City roads (smooth + potholes) / Highways
- Rough roads / cobblestone / broken surfaces
- Speed breakers, rumble strips, sharp curves
- Load conditions (unladen, gross, overload)
- Environmental variations (temperature, wet/dry conditions)
The intent is to gather as much statistically stable and repeatable data for further processing that leads to reliable test and data profiles for further use. The typical results extraction is used by compilation of time histories of multiple sensor / data type and building multiple testing and validation profiles.
Some of the key data processing and consideration methods are Rain flow cycle counting, Peak valley extraction and event-based data identification that accounts for braking, humps and cornering; Each cycle is characterized by amplitude, mean value and frequency of occurrence, forming the basis for fatigue calculations.
In a nutshell, the RLD data determines Critical load paths, Overstressed components, Load asymmetry and some of non-cyclic or unexpected excitations.
NVH being one of the key takeaway components of such a testing, the following parameters are inferred for better design and optimisation processes, these are
- Why certain road inputs cause booming noise or rattles within the cabin
- How road roughness excites body or trim resonances
- Why customer complaints appear only under specific speeds or surfaces
NV Dynamics team conducting RLD testst on GE wind energy component carrier
NV Dynamics conducts a variety of Road Load Testing and data interpretation, mainly focussed on forces and NVH parameters. Consulting and testing services are offered to 2, 4 and multi-wheeler industries; some special and specific RLD tests are also conducted for military applications wherein arsenal is being carried on the vehicle to their deployment locations. We have grown and matured our testing / data analysis methods to help our customer work on the design iterations and optimisation.