Central Vehicle Dynamics Control of the Robotic Research Platform RoboMobil

Bünte, Tilman; Ho, Lok Man; Satzger, Clemens; Brembeck, Jonathan

doi:10.1365/s38314-014-0254-6

Cited by 13 publications

(7 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The FMI (Blockwitz et al, 2012;FMI, 2014) is a standard that enables co-simulation by providing a common interface to couple black box simulators. We focus on FMI based co-simulation, because of its adoption in various fields in industry and academia (Brem-beck et al, 2011;Schweiger et al, 2018a;Bünte et al, 2014;Engel et al, 2018;Sanfilippo et al, 2018;Schweiger et al, 2018b) as well as increasing citations among scientific papers (see Figure 2).…”

Section: Discussionmentioning

confidence: 99%

Proceedings of The American Modelica Conference 2018, October 9-10, Somberg Conference Center, Cambridge MA, USA

2019

Linköping Electronic Conference Proceedings

View full text Add to dashboard Cite

Simulation Led Innovation at Procter & GambleThe required pace of innovation continues to increase in the consumer packaged goods industry. Increasingly historical approaches of development by physical prototypes lead to slow execution, high costs and incremental innovations.By leveraging simulations we can deliver better innovations, faster, at lower costs. Succeeding on this journey requires more than just technical mastery. Changing the way that innovation is done also requires changing how decisions are made and how resources are allocated. It is also necessary to think about the entire lifecycle of the digital assets such as simulation platforms in a manner similar to how we manage our physical assets (e.g. pilot plants). Digital assets required continued funding, maintenance and upgrades to remain viable over time.

show abstract

Section: Discussionmentioning

confidence: 99%

Proceedings of The American Modelica Conference 2018, October 9-10, Somberg Conference Center, Cambridge MA, USA

2019

Linköping Electronic Conference Proceedings

View full text Add to dashboard Cite

show abstract

“…It will also be assumed that the EV is endowed with a vehicle dynamics controller (VDC), responsible for translating the motion demands specified by the driver (e.g., velocities and/or forces) into wheel steering and wheel torque set points, as illustrated in Figure 1 and described in [13], [14]. Based on the wheel torque set points, it becomes necessary to find an appropriate splitting strategy between electric ( ) and friction brake torques ( ), i.e.…”

Section: A Overview Of the Control Systemmentioning

confidence: 99%

“…To design (the scheduling of) the controller's feedback gains we can start by combining (15) together with the linearized plant (14). This gives the characteristic polynomial of this closed loop system.…”

Section: B Controller Designmentioning

confidence: 99%

A model predictive control allocation approach to hybrid braking of electric vehicles

Satzger

Castro

Bünte

2014

2014 IEEE Intelligent Vehicles Symposium Proceedings

Self Cite

View full text Add to dashboard Cite

With the recent emergence of electric drivetrains, a faster and energy efficient braking actuator the electric motor has become available to complement the operation of the traditional friction brakes. The decision on how to split the braking torque among the friction brake and the electric motor is one of the main issues of such hybrid braking systems. With this challenge in mind, a new model predictive control allocation (MPCA) approach for hybrid braking is proposed. In comparison to state of the art torque blending solutions (daisy chain and dynamic control allocation) the MPCA offers faster transient response, without compromising the energy recuperation efficiency of the actuators. In addition, we also develop a linear wheel slip controller to regulate the braking force during emergency braking maneuvers. The tuning of this wheel slip controller is carried out using robust pole placement techniques, which ensures good operation in spite of uncertainties in the tire-road friction coefficient and the vertical load. Simulation results demonstrate the effectiveness of the proposed method.

show abstract

Section: Introductionmentioning

confidence: 99%

Functional Mock-up Interface: An empirical survey identifies research challenges and current barriers

Schweiger¹,

Gomes²,

Engel³

et al. 2019

Linköping Electronic Conference Proceedings

View full text Add to dashboard Cite

Co-simulation is a promising approach for the analysis of complex, multi-domain systems, that leverages mature simulation tools of the respective domains. It has been applied in many different disciplines in academia and industry, with limited sharing of findings. With the increasing adoption of the FMI standard, researchers have set to work on surveying the scattered knowledge on co-simulation in academia. This paper complements the existing surveys by taking on the social and empirical aspect, corroborating, and prioritizing, previous findings. We focus on understanding the perceived research challenges, and the current barriers, based on expert assessment. One of the main barriers pointed out is the limited support for discrete event and hybrid co-simulation.Co-simulation yields multiple advantages: Figure 1. Example master algorithm.

show abstract

Central Vehicle Dynamics Control of the Robotic Research Platform RoboMobil

Cited by 13 publications

References 7 publications

Proceedings of The American Modelica Conference 2018, October 9-10, Somberg Conference Center, Cambridge MA, USA

Proceedings of The American Modelica Conference 2018, October 9-10, Somberg Conference Center, Cambridge MA, USA

A model predictive control allocation approach to hybrid braking of electric vehicles

Functional Mock-up Interface: An empirical survey identifies research challenges and current barriers

Contact Info

Product

Resources

About