Optimization of Running Stability for an Electric SUV

In the development of electric SUV vehicles, particularly range-extended models, significant challenges arise due to differences in vehicle dynamics compared to conventional internal combustion engine vehicles. These electric SUV designs often face issues related to increased mass, altered weight distribution, and modified drivetrain configurations. This paper addresses these challenges through comprehensive theoretical analysis, suspension kinematics and compliance (K&C) evaluation, vehicle handling simulations, and multi-objective optimization of rear suspension characteristics.

The fundamental differences between conventional vehicles and electric SUV models manifest in three primary areas. First, the curb weight increases substantially, particularly in the rear section, leading to a higher rear axle load distribution. Second, the drivetrain configuration changes from front-wheel drive to rear-wheel drive in most electric SUV applications. Third, the instantaneous torque delivery in electric SUV vehicles creates substantial longitudinal forces at the rear wheels, affecting both straight-line and cornering behavior.

To understand these effects quantitatively, we analyze the vehicle dynamics through mathematical modeling. For pitch behavior analysis during acceleration, we consider a simplified trailing arm suspension model. Taking moments about the pivot point A gives us the equilibrium equations:

$$W_{rs}d + \frac{W}{g} \frac{h}{L} a_x d – W_{rs}d – \Delta W_r d – F_{xr} e = 0$$

This simplifies to:

$$\Delta W_r = \frac{W}{g} \frac{h}{L} a_x – F_{xr} \frac{e}{d} = K_r S_r$$

where $W_{rs}$ represents the static rear axle load, $W$ is the total vehicle weight, $\Delta W_r$ denotes the rear wheel load change during acceleration, $F_{xr}$ is the rear wheel longitudinal force, $K_r$ is the suspension stiffness, $S_r$ represents suspension deflection during acceleration, $a_x$ is longitudinal acceleration, $h$ is the center of gravity height, and $L$ is the wheelbase.

For cornering behavior analysis, we employ a bicycle model to derive the longitudinal and lateral forces during steady-state cornering. The sum of longitudinal forces at front and rear wheels is given by:

$$F_{xf} + F_{xr} = F_{lx} – m \frac{v^2}{\rho} \left( \sin \beta – \frac{L_r}{L} \sin \delta \right)$$

The lateral forces at front and rear wheels are expressed as:

$$F_{yf} = \frac{L_r}{L} m v \dot{\psi} + \frac{M_{zf} + M_{zr}}{L} – F_{xf} \sin \delta$$

$$F_{yr} = \frac{L_f}{L} m v \dot{\psi} – \frac{M_{zf} + M_{zr}}{L}$$

These equations demonstrate that rear-wheel drive electric SUV vehicles experience significantly different force distributions compared to their front-wheel drive counterparts, particularly during combined cornering and acceleration maneuvers.

Weight Parameter Comparison Between Conventional SUV and Electric SUV
Parameter Conventional SUV Electric SUV Change
Curb Weight (kg) 2272 2582 310.0
Front Axle Load (kg) 1208 1216 8.0
Rear Axle Load (kg) 1064 1366 302.0
Rear Axle Load Ratio (%) 46.8 52.9 6.1
Center of Gravity Height (mm) 706.5 651.5 -55.0

The increased mass and altered weight distribution in electric SUV vehicles significantly impact handling characteristics. Our simulation studies compared a conventional SUV platform with its electric SUV derivative, maintaining identical suspension hardpoints, components, and tire specifications. The results revealed substantial differences in handling behavior.

Handling Performance Comparison Between Conventional SUV and Electric SUV
Test Condition Metric Unit Conventional SUV Electric SUV
Steady-State Cornering Linear Understeer Gradient (deg)/g 2.991 2.102
Front Axle Cornering Compliance (deg)/g 5.303 5.123
Rear Axle Cornering Compliance (deg)/g 2.312 3.021
Non-linear Front Axle Compliance (deg)/g 9.789 9.209
Non-linear Rear Axle Compliance (deg)/g 3.561 4.065
Straight-Line Acceleration Acceleration Pitch Gradient (deg)/g 2.871 3.493
Front Suspension Lift Gradient mm/g 70.223 91.11
Rear Suspension Compression Gradient mm/g -71.51 -80.272

The suspension K&C analysis revealed critical differences in kinematic behavior between front and rear suspensions. The rear suspension of the conventional platform exhibited characteristics unsuitable for electric SUV applications, particularly regarding anti-squat performance and camber behavior.

Suspension K&C Characteristics Analysis
Property Unit Test Method Front Suspension Rear Suspension
Wheel Travel Toe Gradient (deg)/m Parallel Wheel Travel -7.11 28.613
Wheel Center Longitudinal Displacement Gradient mm/m Parallel Wheel Travel 21.36 48.025
Tire Contact Patch Longitudinal Displacement Gradient mm/m Parallel Wheel Travel 82.445 -473.650
Wheel Travel Camber Gradient (deg)/m Parallel Wheel Travel -9.61 -14.015
Wheel Travel Toe Change Gradient (deg)/m Parallel Wheel Travel -5.439 1.559
Roll Center Height mm Body Roll Motion 88.315 122.5
Wheel Roll Steer Gradient (deg)/100 (deg) Body Roll Motion -7.848 1.868

To address these challenges in electric SUV development, we implemented a comprehensive optimization approach for the rear suspension system. The optimization model was constructed using multi-objective genetic algorithms with specific targets for improved kinematic behavior.

The optimization objectives for the electric SUV rear suspension were defined as follows. First, we targeted the wheel center longitudinal displacement gradient during parallel wheel travel to fall within the range of [-180, -140] mm/m to improve anti-squat characteristics. Second, we aimed to increase the wheel travel camber gradient to the range of [-20, -15] (deg)/m for enhanced cornering stability. Third, we sought to elevate the wheel travel toe change gradient to between [5, 8] (deg)/m to improve transient response.

Constraint management was crucial for the electric SUV development to maintain component commonality. We limited hardpoint modifications to specific locations while ensuring packaging requirements were satisfied for electric motor and battery installation. The design variables selected for optimization included the Z-coordinates of the upper control arm inner point, lower control arm inner point, toe link inner point, and trailing arm body connection point.

Sensitivity analysis revealed the most influential parameters on the target metrics. The wheel travel camber gradient showed high sensitivity to the Z-coordinates of the upper control arm inner and outer points. The wheel travel toe change gradient was primarily affected by the Z-coordinates of the toe link inner point and lower control arm inner point. The wheel center longitudinal displacement gradient demonstrated significant dependence on the Z-coordinates of the trailing arm body connection point and wheel center.

Hardpoint Optimization Results for Electric SUV Rear Suspension
Design Variable Original (mm) Optimized (mm)
Upper Control Arm Inner Point Z-coordinate 191.956 182.151
Lower Control Arm Inner Point Z-coordinate 46.481 51.337
Toe Link Inner Point Z-coordinate 55.693 52.199
Trailing Arm Body Connection Point Z-coordinate 2.500 18.253

The optimization process generated significant improvements in the suspension kinematic characteristics for the electric SUV application. The modified hardpoints produced suspension behavior better suited to the unique requirements of electric SUV vehicles.

Suspension Characteristics Before and After Optimization for Electric SUV
Property Unit Before Optimization After Optimization
Wheel Travel Toe Gradient (deg)/m 58.613 57.654
Wheel Center Longitudinal Displacement Gradient mm/m 28.025 -161.073
Tire Contact Patch Longitudinal Displacement Gradient mm/m -473.650 -429.981
Wheel Travel Camber Gradient (deg)/m -14.015 -18.04
Wheel Travel Toe Change Gradient (deg)/m 1.559 6.124
Roll Center Height mm 122.5 126.2
Wheel Roll Steer Gradient (deg)/100 (deg) 1.868 5.36

Virtual validation through multi-body dynamics simulation demonstrated substantial improvements in the electric SUV handling characteristics. The optimized suspension configuration restored the understeer gradient to levels comparable with the conventional vehicle while improving rear axle cornering compliance.

Handling Performance Comparison After Electric SUV Suspension Optimization
Test Condition Metric Unit Conventional SUV Electric SUV Before Optimization Electric SUV After Optimization
Steady-State Cornering Linear Understeer Gradient (deg)/g 2.991 2.102 2.749
Front Axle Cornering Compliance (deg)/g 5.303 5.123 5.203
Rear Axle Cornering Compliance (deg)/g 2.312 3.021 2.454
Non-linear Front Axle Compliance (deg)/g 9.789 9.209 9.227
Non-linear Rear Axle Compliance (deg)/g 3.561 4.065 3.711
Straight-Line Acceleration Acceleration Pitch Gradient (deg)/g 2.871 3.493 2.14
Front Suspension Lift Gradient mm/g 70.223 91.11 75.613
Rear Suspension Compression Gradient mm/g -71.51 -80.272 -30.39

Physical validation through prototype vehicles confirmed the simulation results. Subjective evaluation by experienced test drivers noted significant improvements in the electric SUV handling characteristics, particularly in understeer behavior, rear axle grip, and vehicle stability during transient maneuvers. The optimized electric SUV demonstrated handling qualities approaching those of the conventional vehicle while maintaining the benefits of electric propulsion.

The development process for electric SUV vehicles requires careful attention to suspension kinematics, particularly when adapting conventional platforms. The increased mass, altered weight distribution, and rear-wheel-drive configuration of electric SUV vehicles demand specific suspension characteristics that differ from conventional front-wheel-drive vehicles. Through targeted optimization of suspension hardpoints, we achieved substantial improvements in electric SUV handling while maintaining component commonality where possible.

Future electric SUV development would benefit from dedicated platform designs rather than adaptations of conventional vehicle architectures. This approach would allow for optimized packaging of electric powertrain components while providing greater flexibility in suspension geometry design. The methodologies presented here provide a framework for developing capable and predictable handling characteristics in electric SUV vehicles, contributing to the advancement of sustainable mobility solutions.

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