⚡ electrical engineering

Influence of Air Spring Pressure on Ride Comfort and Dynamic Response of an Electric Vehicle under Random Road Excitation

This study investigates how varying air spring pressures affect the ride comfort and dynamic response of electric vehicles on random road excitation, revealing that higher pressures increase suspension stiffness and wheel loads while reducing comfort, thereby identifying optimal pressure ranges to balance these competing factors across different road classes and speeds.

Original authors: Nguyen Thanh Tung, Luong Van, Khau Tan Phat, Nguyen Thanh Danh, Phan Chuong Anh Khoi

Published 2026-10-05

📖 5 min read🧠 Deep dive

CC BY 4.0

Original authors: Nguyen Thanh Tung, Luong Van, Khau Tan Phat, Nguyen Thanh Danh, Phan Chuong Anh Khoi

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Every vehicle that travels on a road must negotiate a constant battle between two competing needs. The first is the need to isolate the passengers from the rough, uneven texture of the pavement, keeping the ride smooth and comfortable. The second is the need to keep the tires firmly pressed against the ground, ensuring that the vehicle can steer, brake, and accelerate safely. If a suspension system is too soft, the car might feel like a boat on a wave, isolating the driver from the road but risking a loss of control when the tires bounce. If the system is too stiff, the tires stay planted, but every bump is transmitted directly to the passengers, turning a drive into a jarring experience. For electric vehicles, this balance is even more delicate because the heavy battery packs and unique motor configurations change how the car weighs and moves, making the traditional settings for suspension less effective.

In a recent study, researchers set out to find the precise balance for electric vehicles equipped with air springs. Unlike traditional steel springs, which have a fixed stiffness, air springs use compressed gas to support the vehicle's weight. By changing the pressure of this gas, engineers can alter how stiff or soft the suspension feels. The team from Vinh Long University of Technology Education in Vietnam investigated how different levels of air pressure affect a vehicle driving over roads of varying quality, from smooth highways to extremely rough tracks. They simulated the vehicle traveling at speeds between 30 and 60 kilometers per hour on four distinct types of road surfaces, ranging from good to extremely poor. Their goal was to determine the ideal pressure settings that would keep the ride comfortable without sacrificing the safety of the tire's contact with the road.

The researchers built a detailed digital model of an electric vehicle, treating it as a complex system with seven moving parts to capture how the body and wheels react to bumps. They subjected this virtual car to random vibrations that mimic real-world driving conditions, testing four specific air pressure levels: 400,000, 600,000, 800,000, and 1,000,000 Pascals. As they increased the pressure, the air inside the springs became harder to compress, effectively making the suspension stiffer. The results were clear and consistent across all road types: higher pressure led to a rougher ride. When the pressure was at its lowest, the vehicle absorbed the bumps well, but as the pressure rose to its maximum, the vehicle body began to shake more violently. On the smoothest roads tested, increasing the pressure from the lowest to the highest setting caused the average vibration felt by the passengers to jump by nearly 41 percent.

This increase in stiffness also had a direct impact on how the tires interacted with the road. While a stiffer suspension might seem like it would keep the tires planted, the simulations showed the opposite effect on rough terrain. As the pressure increased, the tires were more likely to bounce and lose contact with the ground, especially at higher speeds. The researchers measured this using a factor that indicates how much the weight on the tire fluctuates. On the roughest roads, when the vehicle was traveling fast with high air pressure, the tires came dangerously close to lifting off the surface entirely. This loss of contact is critical because a tire that is not touching the road cannot steer or brake effectively. The study found that on the most uneven surfaces, the highest pressure settings reduced the tire's grip significantly, creating a scenario where the vehicle might become unstable.

The quality of the road surface played a massive role in how these pressure settings performed. On smooth, high-quality roads, the vehicle could tolerate a wider range of pressures, with settings between 400,000 and 800,000 Pascals offering a reasonable compromise between comfort and safety. However, as the road surface became rougher, the margin for error shrank. On medium-quality roads, the researchers recommended lowering the pressure to between 400,000 and 600,000 Pascals to maintain safety. On the very poor and extremely rough roads, the simulations suggested that the lowest pressure setting was the only way to keep the ride tolerable and the tires in contact with the ground. In these harsh conditions, driving at high speeds combined with high air pressure created a perfect storm of discomfort and danger, with the vehicle body shaking violently and the tires struggling to maintain grip.

The study also highlighted that the relationship between speed and pressure is not linear. Driving faster on a rough road with a stiff suspension amplifies the negative effects, causing the vehicle to bounce more and the tires to lose contact more frequently. The researchers noted that while their findings provide a clear guide for these specific conditions, they are based on computer simulations rather than physical road tests. The model did not account for every possible variable, such as changes in the vehicle's cargo load or the complex heat dynamics inside the air springs. Nevertheless, the results offer a practical roadmap for engineers and drivers. They suggest that for electric vehicles to remain comfortable and safe, the air pressure in the suspension should not be set to a single fixed value. Instead, it should be adjusted dynamically, lowering the pressure as the road gets rougher or the vehicle speeds up, ensuring that the car remains a stable platform for its passengers while keeping its feet firmly on the ground.

Technical Summary: Influence of Air Spring Pressure on Ride Comfort and Dynamic Response of an Electric Vehicle under Random Road Excitation

Problem Statement
The study addresses the critical challenge of optimizing ride comfort and dynamic safety in electric vehicles (EVs) equipped with pneumatic (air) suspension systems. Unlike conventional steel springs with fixed stiffness, air suspensions offer adjustable stiffness via internal gas pressure. However, the specific influence of air spring pressure on EV dynamics—particularly given the unique mass distribution caused by heavy battery packs and potential wheel-mounted motors increasing unsprung mass—remains under-explored under random road excitation. The research aims to determine how varying air spring pressures affect vehicle body acceleration (ride comfort) and dynamic wheel loads (tire-road contact capability) across different road roughness classes (ISO 8608:2016 B, C, D, and E) and vehicle speeds (30–60 km/h).

Methodology
The authors developed a seven-degree-of-freedom (7-DOF) dynamic model of an electric vehicle. The model includes:

Sprung Mass: Three degrees of freedom representing vertical translation ( $Z$ ), roll ( $\phi$ ), and pitch ( $\beta$ ).
Unsprung Masses: Four degrees of freedom representing the vertical motion of the front-left, front-right, and rear axle masses, plus the rear axle's roll motion.

The pneumatic suspension system was modeled using equivalent stiffness and damping coefficients derived from air volume, auxiliary chambers, and pipework flow characteristics. The vehicle was subjected to random road excitations generated according to ISO 8608:2016 standards for road classes B (good) through E (extremely poor).

Simulations were conducted to evaluate two primary performance metrics:

RMS Vehicle Body Acceleration ( $\ddot{Z}_{RMS}$ ): Used as the primary indicator for ride comfort.
Dynamic Load Coefficient ( $k_d$ ): Calculated as the ratio of dynamic wheel load to static wheel load. $k_{dmax}$ indicates peak dynamic loading, while $k_{dmin}$ assesses the risk of tire-road separation (loss of contact).

The study varied air spring internal pressures from $4 \times 10^5$ Pa to $10 \times 10^5$ Pa and vehicle speeds from 30 km/h to 60 km/h.

Key Results
The simulation results revealed consistent trends across all road classes:

Effect of Pressure on Stiffness and Comfort: Increasing air spring pressure increases the equivalent stiffness of the suspension system. Consequently, higher pressures lead to significantly higher RMS vehicle body acceleration, reducing ride comfort. For instance, on Class B roads at 60 km/h, increasing pressure from $4 \times 10^5$ Pa to $10 \times 10^5$ Pa raised body acceleration by approximately 41% (from 0.144 m/s² to 0.203 m/s²).
Effect of Pressure on Dynamic Loads: Higher air spring pressure increases the maximum dynamic load coefficient ( $k_{dmax}$ ) and decreases the minimum coefficient ( $k_{dmin}$ ). This indicates that stiff suspensions transmit more road-induced forces to the vehicle body and reduce the tire's ability to maintain continuous contact with the road surface.
Impact of Road Roughness and Speed: The adverse effects of high pressure are amplified by road roughness and vehicle speed.
- Class B (Good): Optimal pressure range identified as $4 \times 10^5$ to $8 \times 10^5$ Pa.
- Class C (Medium): Performance deteriorates; a lower range of $4 \times 10^5$ to $6 \times 10^5$ Pa is recommended to maintain safety.
- Class D (Bad) & E (Extremely Poor): Dynamic performance degrades significantly. On Class E roads at 60 km/h and $10 \times 10^5$ Pa, body acceleration reached 0.930 m/s², and $k_{dmin}$ dropped to 0.105, indicating a severe risk of tire separation. For these conditions, lower pressures ( $4 \times 10^5$ Pa) and reduced speeds are necessary.
Axle Uniformity: The study found negligible differences between front and rear axle responses, suggesting the model's load distribution and suspension characteristics were uniform across axles.

Significance and Claims
The paper claims to provide practical guidance for selecting air spring pressures in air-suspended electric vehicles operating under random road excitation. The authors emphasize that pressure should be treated as an optimal design variable rather than just an operating parameter. The study identifies specific pressure ranges that offer a compromise between ride comfort and tire-road contact capability for different road conditions:

Class B: $4 \times 10^5$ – $8 \times 10^5$ Pa.
Class C & D: $4 \times 10^5$ – $6 \times 10^5$ Pa.
Class E: Lower pressures are preferable, particularly at higher speeds.

Limitations
The authors explicitly acknowledge several limitations to their findings:

Model Validation: The results are based on a numerical 7-DOF model and have not yet been validated through full-scale road tests or experimental measurements.
Model Simplification: The air spring is represented by an equivalent stiffness model. Complex nonlinear effects, such as thermodynamic heat transfer, hysteresis, throttling losses, and pressure-dependent damping, were not explicitly included.
Fixed Configuration: The analysis assumes a fixed vehicle configuration and does not investigate the effects of payload variations, which could influence optimal pressure settings.
Evaluation Criteria: The study relies solely on RMS body acceleration and the dynamic load coefficient, excluding other potential ride comfort or handling metrics.

The paper concludes that while the identified pressure ranges provide a reasonable compromise for the specific vehicle model and conditions studied, they should not be regarded as universal optimum values without further experimental validation and consideration of nonlinear dynamics.

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