Study on handling assist control based on rear wheel sideslip angle

Naoto Ohkubo･Ryo Koyama･Fumiaki Honjo (Honda Moter)

In order to make it easier for the driver to trace the desired driving line even on slippery road surfaces, rear wheel sideslip angle feedback control that applies restoring yaw moment based on the rear wheel sideslip angle obtained from the estimator has been devised. The control effectiveness was confirmed through simulation and actual vehicle tests.

Study on roll behavior and improvement of dynamic cornering characteristics with front-rear relative roll angular velocity compensation control

Toshiki Matsumoto (Advanced Technology Development Division Integrated Application Development Dept.)･Yosuke Yamada (Product Validation Dept.)

Focusing on the fact that the relative transient behavior of the front and rear roll motion of the vehicle body, which is caused by the rigidity of the vehicle body, affects the “feel of connectedness" at the initial steering and the "predictability" during cornering, etc., we verified the effect of improving roll behavior and maneuverability characteristics during cornering with front-rear relative roll angular velocity compensation control using a variable damping force suspension (AVS).

Application of Data-Based Preview Controller to Torsion Bar Active Suspension

Hiroki Furuta･Jin Hozumi･Takashi Saito･Tatsuya Keida (Toyota Motor)

Torsion bar active suspension with using electronic motor is environmentally friendly and has advantage in cost because it is oil-less and possible to share parts with other chassis components. However, it has disadvantage in response, therefore in this paper, data-based preview controller proposed by us is applied to the torsion bar active suspension to improve control effectiveness.

Study on Self-optimizing Traction Control by Estimating Road Friction and Application to Autonomous Lawnmower

Kyohei Sakagami･Akiko Ito (Honda R&D)･Takayuki Arakawa･Yuichi Kawasaki (Honda Motor)

Autonomous lawnmowers require more accurate tracking than passenger cars, because even the slightest path error can result in grass being left uncut. Sudden changes in traction force can damage the grass, therefore, this problem cannot be solved by simply improving sensor accuracy or increasing control gain. In this paper, we propose a method to estimate road frictional coefficient based on the vehicle and traction force model and optimize the traction force of the left and right wheels.