The McPherson suspension represents a landmark in automotive engineering, pioneered by Earle S. MacPherson during his tenure at General Motors in the 1930s (Evangelisti, 2025). Originally conceived for compact cars targeting sub-one-ton curb weights, the design consolidated the shock absorber and steering pivot into a unified strut assembly, eliminating the need for separate upper control arms. This innovation achieved remarkable space efficiency, reduced component count by approximately 30% compared to double-wishbone architectures, and delivered satisfactory ride comfort and handling characteristics for mainstream applications (Hu et al., 2025).

The fundamental configuration comprises three primary components: a telescopic shock absorber housing that doubles as the steering kingpin, a coaxial coil spring, and an A-shaped lower control arm (LCA) connecting the knuckle to the subframe (Lanni et al., 2024). Most variants incorporate a stabilizer bar linking the LCAs to mitigate body roll. The mechanism’s kinematic behavior is characterized by wheel alignment parameters—camber, toe, caster, and kingpin inclination—that vary nonlinearly with wheel travel, fundamentally influencing tire wear, steering feel, and lateral stability (Hamza et al., 2024).

The McPherson suspension operates as a spatial mechanism where the strut’s sliding motion combined with LCA rotation guides vertical wheel movement. The instantaneous center of rotation is determined by the LCA pivot geometry and strut inclination, directly affecting the roll center height and camber gain characteristics. Unlike double-wishbone designs offering independent control of camber and kingpin geometry, McPherson’s integrated structure imposes inherent coupling constraints, resulting in compromised camber control during cornering and accelerated tire wear under aggressive driving.

However, this coupling proves advantageous for NEV applications where packaging constraints are severe. The compact strut assembly accommodates front-drive motors and steering gear within minimal lateral space, while the high-mounted spring facilitates low hood lines critical for aerodynamic efficiency (Kim et al., 2012). The system’s natural frequency, typically 1.1–1.3 Hz for passenger cars, can be tuned through spring stiffness and motion ratio adjustments to compensate for increased NEV mass without substantially enlarging components.

NEVs exhibit fundamentally different weight distributions compared to internal combustion vehicles. Battery packs mounted beneath the passenger compartment lower the center of gravity (CoG) by 50–100 mm but increase sprung mass by 200–400 kg, imposing severe loads on suspension components (Choi and Han, 2007). For McPherson systems, this translates to heightened bending moments on the strut assembly and increased LCA fatigue stresses. Static deflection under full battery load can exceed 40 mm, necessitating stiffer springs that compromise ride comfort if not properly calibrated (Uys et al., 2007). The mass penalty directly impacts energy consumption; a 10% weight reduction yields approximately 6%–8% improvement in driving range (Gordienko et al., 2006). Consequently, NEV chassis design prioritizes light weighting strategies, targeting 15%–25% mass reduction in upsprung components. McPherson LCAs, traditionally fabricated from stamped steel, are prime candidates for aluminum conversion or composite reinforcement, achieving 30%–40% weight savings while maintaining structural integrity (Krishna et al., 2005). The elimination of engine noise elevates road-induced NVH to primary prominence in NEV passenger experience. McPherson strut bushings and top mounts become critical transmission paths for high-frequency vibrations (80–300 Hz) from tire-road interaction, requiring advanced rubber compounds and hydraulic damping elements (Sprang et al., 1996). Audi’s Q4 e-tron implements multi-layer acoustic glass and foam-filled tires to attenuate noise transmitted through the McPherson front axle, achieving 3 dB(A) interior noise reduction compared to conventional implementations (Simon et al., 2010). Furthermore, electric motor torque ripple and gear whine introduce new vibration sources within the 200–2000 Hz range, demanding redesigned subframe isolation strategies. Hyundai’s INSTER employs reinforced body sealing and thickened door glass, complementing the McPherson suspension’s inherent NVH characteristics to deliver premium-segment quietness (Meek et al., 2013). Active noise cancellation systems integrated with suspension controllers can further mitigate tonal disturbances by phase-inverting strut-transmitted vibrations (Wang and Kennedy, 2025). The key parameters of suspension design between internal combustion engine vehicles and new energy vehicles are shown in Table 1.

The complexity of NEV suspension tuning necessitates advanced optimization beyond traditional trial-and-error methods pioneered genetic algorithm (GA) application to electric vehicle McPherson design, minimizing front wheel alignment parameter variation and tire lateral slip through coordinated hardpoint coordinate adjustments (Liu et al., 2013). Their two-stage optimization reduced camber change by 42% and scrub radius variation by 38% during 80 mm wheel travel, substantially improving tire longevity and steering precision. Recent developments employ improved artificial fish swarm algorithms (IAFSA) to concurrently optimize suspension and seat parameters, achieving 15.4% reduction in driver seat acceleration and 11.5% improvement in body vertical dynamics for Class-B Road profiles at 20 m/s (GonAlves and Ambrósio, 2003). AI-driven approaches promise further enhancements; quantum-inspired optimization algorithms demonstrate superior Pareto front exploration efficiency compared to conventional GA, potentially reducing computational cost by 60% for high-dimensional design spaces.

Multi-body dynamics simulation via ADAMS/Car has become indispensable for NEV suspension development, enabling parametric modeling of complex interactions between battery mass distribution and kinematic performance (Hmida et al., 2025). Established a micro-EV McPherson model validating against physical K&C (kinematics and compliance) test data, achieving <10% error in camber and toe curves across full travel range (Sun et al., 2023). Sensitivity analysis identifies critical coordinates influencing kingpin inclination and caster, guiding optimization focus to high-impact parameters. Topology optimization emerges as a powerful tool for component lightweighting. Dikmen et al. applied density-based topology optimization to a McPherson lower wishbone converted for EV application, achieving 22% mass reduction while satisfying durability and stiffness constraints. Integration of finite element analysis (FEA) with multi-body dynamics enables simultaneous structural and kinematic optimization, streamlining development cycles critical for fast-paced NEV product launches.

A quantitative comparison of the core optimization technologies for NEV McPherson suspension and their key convergence parameters can intuitively reflect the performance differences and engineering application value of various methods, with the specific results summarized in Table 2. It can be seen from the table that GA + AI hybrid optimization (quantum-inspired) exhibits comprehensive advantages in optimization performance, convergence efficiency and adaptability to NEV multi-constraint requirements, and is the most suitable core optimization technology at this stage, while other technologies have obvious limitations in global optimization, parameter coverage and convergence efficiency, and are more suitable as auxiliary means for specific performance improvement.

The transition from steel to aluminum for McPherson LCAs offers compelling benefits for NEVs. A comparative FEA study on an EV McPherson arm demonstrated that aluminum (6061-T6) constructions reduce mass by 34% while maintaining comparable static strength, though requiring 2.5 mm increased thickness to offset lower modulus. Dynamic performance improvements include reduced upsprung mass, enhancing road holding and enabling downsized actuators in active variants. Audi’s Q4 e-tron employs aluminum-intensive McPherson strut components, including knuckles and LCAs, contributing to a 15% front-axle weight reduction versus steel-intensive architectures. However, aluminum’s lower fatigue strength necessitates redesigned load paths and increased section moduli, often validated through accelerated life testing correlating with multi-body simulation load spectra. Fiber-reinforced polymers (FRP) represent the next frontier for McPherson lightweighting. Belin Gardi et al. developed a short glass-fiber reinforced polyamide (PA66) LCA through integrated product-process digitalization, achieving 45% mass savings versus steel baseline. The hybrid metal-composite design, featuring over-molded polymer on steel inserts, addresses difficult-to-model constraint behaviors while providing superior corrosion resistance critical for NEVs operating in varied climates. Manufacturing challenges include weld line management, creep behavior at elevated temperatures, and dynamic strength validation. Industry 4.0 paradigms enable real-time process monitoring to ensure consistent fiber orientation and minimize voids, achieving production-scale feasibility for volumes exceeding 100,000 units annually.

The electrification of powertrains facilitates integration of active suspension technologies previously constrained by parasitic energy consumption. Linear motor electromagnetic suspensions replace conventional dampers, enabling millisecond-level force control while harvesting vibration energy. Zuo et al. demonstrated a McPherson-derived electromagnetic suspension recovering 26–33 W average power under Class-C Road excitation while reducing body acceleration by 14.7%.

Hybrid architectures combining passive hydraulic damping with active electromagnetic elements optimize the trade-off between energy consumption and dynamic performance. Ding et al.'s hybrid actuator achieves 67.8% energy reduction versus pure active systems while maintaining comparable ride comfort improvements, addressing critical NEV range preservation concerns. Advanced control algorithms transform McPherson suspension responsiveness. Model Predictive Control (MPC) leverages preview road data from front-mounted cameras to preemptively adjust damping, reducing impact harshness by 30% in validation studies. Machine learning approaches enable real-time adaptation to driver behavior and road conditions; reinforcement learning agents trained on diverse terrain databases outperform fixed-gain controllers in comfort-handling compromise metrics. Integration with vehicle dynamics controllers (VDC) enhances safety. During regenerative braking, McPherson strut compression can be actively managed to maintain optimal tire contact patch, preventing wheel lock-up and improving energy recovery efficiency by 8%–12%. This synergetic control exemplifies the holistic optimization potential in NEV architectures.

Despite advancements, fundamental McPherson limitations persist. The inherent camber loss during body roll (typically −0.8°/g lateral acceleration) accelerates outer tire wear and reduces cornering grip compared to double-wishbone alternatives. For NEVs with high instantaneous torque, this deficiency becomes pronounced during rapid lane changes, necessitating supplementary chassis interventions. The elevated roll center required for battery clearance can induce jacking forces, particularly in vehicles with >300 mm ground clearance for off-road capability. Mitigation through LCA geometry revision often compromises anti-dive characteristics during heavy regenerative braking.

Future McPherson evolution converges on intelligent, integrated systems. Electromagnetic energy-regenerative dampers are poised for commercialization, with suppliers like Monroe delivering CVSA2 dual-valve technology enabling independent rebound/compression control, specifically targeting EV applications due to minimal power consumption (<10 W average).

Quantum computing optimization promises to revolutionize suspension design, potentially evaluating 10⁶ parameter combinations within hours versus weeks for conventional methods. When coupled with digital twin technologies, this enables continuous in-service optimization, adapting to individual driving patterns and battery degradation-induced weight changes.

Cell-to-chassis (C2C) architectures present both opportunities and challenges. Integrating battery packs as structural members could reduce overall vehicle mass by 10%, but requires McPherson hardpoints to accommodate increased chassis stiffness (targeting >30,000 N·m/deg torsional rigidity) and thermal expansion mismatches. Advanced adhesives with >15 MPa bond strength and elastomeric isolation layers will be critical for maintaining suspension kinematic accuracy.