Taking inspiration from the animal kingdom, it is easy to point out weaknesses in the dynamics of land-based vehicle control. As a cheetah runs, it requires the combined inputs of visual prediction, tactile sense and inherent habit. Using these inputs, the animal can adjust pressure points on specific parts of each foot, thereby shifting weight distribution and maximizing tractive force under all conditions. It is able to adapt to uneven terrain while keeping the head nearly level for ideal tracking.
An automobile, adversely, does none of these things. The most sophisticated suspension systems currently in use allow for the adjustment of damping and resistive levels, as well as ride height such as the optional Model S air suspension. This system lacks the additional ability to control individual contact point pressures. This decreases the capability for the Model S to manage variations in road conditions under high performance operation.
Imagine a blind cheetah. Operating at 60 miles per hour without a clue what it will be stepping on; not a recipe for success. It is likely to break a leg due to the jarring effects of a badly timed step. The automobile of today is blind to upcoming terrain, leading to the common effect of damaging suspension components and performing poorly.
Suspension in vehicles has not fundamentally changed since the leather and wood leaf springs of ancient Rome. The same leaf spring used in horse-drawn carriages still finds a place in heavy utility vehicles being produced today. Advancements since the industrial era have been found in the form of MacPherson struts, independent coilovers and multi-links in various arrangements to ensure the weight of a vehicle is shifted smoothly and evenly under high-G acceleration.
Currently, the German luxury trio of Mercedes-Benz, Audi and BMW have released limited systems utilizing active suspension systems. Most other auto manufacturers have ongoing developments as well. Many of these attempt to reactively adjust suspension components in response to just tactile feedback. A few are trying to implement linear electromagnetic generators to both control damping and generate electricity from the force of bumps. Of all released systems, Audi has the most progressive system detailed conceptually in a non-technical public video (Available here). Audi utilizes a front-facing camera to scan the road ahead in a narrow FOV and develop a depth-point map. This data gets built into a 3D model of upcoming road conditions which they then use to adjust suspension damping before the terrain is met.
A famous development by Bose Corporation engineers is the full-control electromagnetic suspension. Bose developed linear electromagnetic motors capable of providing enough force to raise an entire vehicle (Available here). Using proprietary control algorithms, the LEMs were installed as suspension components in a test vehicle.The Bose linear electromagnetic motors are used in a modified MacPherson strut-type layout. The lower suspension arms and rack-and-pinion steering system attach to an aluminum engine cradle that bolts directly to the car body. Each front wheel is fully independent, since no anti-roll bars are required.
This vehicle displayed marvelous capabilities in dynamic response. The wheels can apply pressure nearly independently of the body allowing for nearly level cornering, acceleration and braking. In the linked video, it was shown that the Lexus sedan could be made to jump over a curb entirely, using a hard-coded signal to the four LEMs. However, the system was almost entirely abandoned due to the inherent power issues of having large LEMs in a gasoline vehicle. A generator was required to run inside to provide suitable electrical power.
Over the past ten years, the rapid improvement in electric vehicles (due to battery technology and the associated power electronics) has led to a reconsideration of the usage of active suspension. Furthermore, more efficient linear electromagnetic motors have lowered power demands, such as the SKF design developed at the Eindhoven University of Technology.
With this project, we aim to investigate the performance of an active suspension when used in conjunction with another rapidly improving technology - 3D machine vision. With increasing mobile computing power and improved sensors, we can now effectively implement 3D machine vision in a suitably small package for low-cost testing. On top of that, vehicles will soon be utilizing LIDAR systems more commonly for autonomous driving - these can be utilized for preview control algorithms to manipulate an active suspension system.
It is a better time than ever before to consider the usage of vision-based active suspension for a vehicle. In the next post, we'll discuss how our student team aims to implement these concepts into a test prototype.