Electro-Pneumatic Air Shock Optimization System with User Specified Parameters and Integrated Driver Control for Off Road Vehicles - Senior Design

Problem & Concept

This two-semester senior design project developed an electro-pneumatic air-shock optimization system designed to retrofit onto off-road vehicles equipped with air shocks. Unlike traditional setups, which require drivers to stop, exit the vehicle, and manually adjust shock pressures with a pump or compressor, the system enables near-instantaneous adjustment at the push of a button. The design integrates pneumatics, electronics, and computing into a cohesive package: a compressor supplies air, solenoid valves direct flow, pressure sensors monitor conditions, and a Raspberry Pi/Arduino pair governs operation through custom control software. The system was conceived as a vehicle-agnostic aftermarket kit, adaptable to UTVs, ATVs, and other platforms with air shocks. Testing was performed on Fairfield University’s 2022 Baja vehicle as a proving platform, but the concept is broadly applicable. The final product achieved dynamic pressure regulation accurate to within ±5 psi, with setpoint changes completed in under one second. In suspension travel testing, error was reduced by up to 77% compared to baseline, demonstrating a measurable performance benefit. Equally important, the project cultivated advanced technical and professional skills. It required cross-disciplinary collaboration between mechanical engineers and computer scientists, rapid self-directed learning in pneumatics and embedded computing, and the ability to deliver a robust, user-ready product under time and budget constraints. These experiences mirror real-world product development, where mechanical, electrical, and software considerations must be integrated seamlessly.

System Architecture

The system architecture integrated three subsystems: pneumatic, electronic, and computing. Pneumatically, a 1.6-gallon onboard compressor provided pressurized air through a regulator and high-pressure tubing rated to 300 psi. At each vehicle corner, solenoid valves controlled fill, exhaust, and hold functions, enabling rapid pressure adjustment. Pressure transducers continuously measured chamber pressure, supplying real-time feedback. Electronically, the 12 V solenoids were actuated via relays triggered by a Raspberry Pi’s low-voltage output. The Raspberry Pi itself handled computation, user interface logic, and preset selection. Because it cannot natively process analog inputs, an Arduino was integrated as an analog-to-digital converter, bridging sensor data to the Pi . From the driver’s perspective, a steering-wheel-mounted module with push buttons and toggle switches provided intuitive inputs. The interface enabled manual adjustment, preset selection, and system status monitoring on a digital screen. Importantly, redundancy was built in: if the system was switched off or an error occurred, pressures reverted to a safe neutral setting. This fail-safe architecture ensured operational reliability while providing advanced functionality.

Control Software & Algorithms

Custom software written in Python and C++ orchestrated the interaction between sensors, solenoids, and the driver interface. The control logic implemented a closed-loop feedback system that compared measured pressure to setpoints and actuated valves in rapid sub-second bursts to approach targets without overshoot. The program filtered out short-lived spikes caused by bumps or compression events, ensuring stable operation only when the vehicle was in steady-state load. Presets were stored in the Raspberry Pi, with up to eight unique configurations available. Drivers could toggle between them instantly, with each preset corresponding to different terrain requirements. Logic statements ensured graceful handling of errors, such as invalid input or hardware miscommunication, defaulting the system to neutral pressures rather than shutting down. This emphasis on robust coding highlighted the importance of error handling, real-time data filtering, and user-centered interface design in embedded systems .

Driver Interface

A compact digital display mounted on the steering wheel provided real-time visibility of shock pressures, preset selection, and system state. Four tactile buttons enabled quick access to presets, while toggle switches managed power and mode selection. The interface was deliberately designed for low cognitive load in high-vibration conditions, emphasizing legibility and minimal glance time.From the driver’s perspective, the value of the system was immediate: instead of stopping to adjust shocks, terrain-specific profiles could be engaged on the fly. For instance, a driver could soften suspension before tackling rocks, then stiffen it again for higher-speed sections of trail. This ability to reconfigure suspension dynamically translated into measurable improvements in comfort, stability, and performance.

Testing & Results

Testing followed three stages: static validation, dynamic evaluation, and performance benchmarking. In static trials, the system demonstrated pressure regulation accuracy within ±5 psi across all four shocks. In dynamic use, spike filtering and rapid actuation ensured stability even under demanding terrain inputs. Performance testing on the Baja vehicle showed quantifiable gains. Suspension travel error decreased from 130% baseline to 11.8% in the front and from 107% to 35% in the rear, yielding a 77% overall improvement in suspension performance . The system’s rapid response (<1 second) and reliable regulation underscored its practical effectiveness. Beyond numbers, the system provided a transformative user experience: shocks could be tuned mid-course, eliminating the downtime associated with manual adjustments.

Skills Learned

This project demanded systems-level engineering, spanning pneumatics, electronics, computing, and user interface design. Mechanically, it deepened expertise in shock dynamics, pneumatic control, and packaging components for durability in vibration- and heat-intensive environments. Electrically, it provided experience with relays, power management, analog-to-digital conversion, and integration of low- and high-voltage subsystems. On the software side, it strengthened embedded programming in Python and C++, with a focus on control algorithms, state machines, and user-interface logic. Equally important were the professional and managerial skills developed. The project required cross-disciplinary collaboration between mechanical engineers and computer scientists, emphasizing communication across specialties and clear delegation of tasks. Budget management ($3,000 funding across INSPIRE and NASA grants) and schedule adherence underlined real-world constraints . Design decisions were guided by considerations of safety, manufacturability, and future scalability, aligning with professional engineering practice. The final system was not only technically successful but also market-relevant. By demonstrating significant performance improvements and real-time adaptability, the project delivered a working proof-of-concept for a commercializable kit. In doing so, it highlighted skills essential to engineering careers: identifying needs, creating solutions, validating performance, and integrating diverse technologies into a cohesive, reliable product.