Control of Integrated Powertrain With Electronic Throttle and Automatic Transmission

Kim, Daekyun; Peng, Huei; Bai, Shoumei; Maguire, Joel

doi:10.1109/tcst.2007.894641

Cited by 112 publications

(63 citation statements)

References 8 publications

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“…For adaptive cruise control in particular, numerous works already exist that realize a commanded acceleration, see e.g. [27], [28]. The effects of engine characteristics in terms of fuel consumption can be considered in the cost function (see Sec.…”

Section: Vehicle Modelsmentioning

confidence: 99%

See 1 more Smart Citation

CommonRoad: Composable benchmarks for motion planning on roads

Althoff

Koschi

Manzinger

2017

2017 IEEE Intelligent Vehicles Symposium (IV)

298

166

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Abstract-Numerical experiments for motion planning of road vehicles require numerous components: vehicle dynamics, a road network, static obstacles, dynamic obstacles and their movement over time, goal regions, a cost function, etc. Providing a description of the numerical experiment precise enough to reproduce it might require several pages of information. Thus, only key aspects are typically described in scientific publications, making it impossible to reproduce results-yet, reproducibility is an important asset of good science. Composable benchmarks for motion planning on roads (CommonRoad) are proposed so that numerical experiments are fully defined by a unique ID; all information required to reconstruct the experiment can be found on the CommonRoad website. Each benchmark is composed by a vehicle model, a cost function, and a scenario (including goals and constraints). The scenarios are partly recorded from real traffic and partly hand-crafted to create dangerous situations. We hope that CommonRoad saves researchers time since one does not have to search for realistic parameters of vehicle dynamics or realistic traffic situations, yet provides the freedom to compose a benchmark that fits one's needs.

show abstract

Section: Vehicle Modelsmentioning

confidence: 99%

“…• Energy: J E = t f t0 P (x(t), u(t)) dt, where P (x(t), u(t)) is the required power of the engine for the state x and the input u, which can be obtained from engine mappings (see [28,Sec. …”

Section: Iiib])mentioning

confidence: 99%

CommonRoad: Composable benchmarks for motion planning on roads

Althoff

Koschi

Manzinger

2017

2017 IEEE Intelligent Vehicles Symposium (IV)

298

166

View full text Add to dashboard Cite

show abstract

“…Optimal gear selection in internal combustion engine vehicles is a wellstudied problem (Kim et al, 2007), but what is less clearly understood is if drivers can speed up or down to augment the transmission's ability to put the engine in a higher efficiency mode of operation. Many factors affect a vehicle's fuel consumption.…”

Section: Fleet Ecodriving Use Casementioning

confidence: 99%

Cloudthink: A Scalable Secure Platform for Mirroring Transportation Systems in the Cloud

et al. 2015

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Abstract. We present a novel approach to developing a vehicle communication platform consisting of a low-cost, open-source hardware for moving vehicle data to a secure server, a Web Application Programming Interface (API) for the provision of third-party services, and an intuitive user dashboard for access control and service distribution. The CloudThink infrastructure promotes the commoditization of vehicle telematics data by facilitating easier, flexible, and more secure access. It enables drivers to confidently share their vehicle information across multiple applications to improve the transportation experience for all stakeholders, as well as to potentially monetize their data. The foundations for an application ecosystem have been developed which, taken together with the fair value for driving data and low barriers to entry, will drive adoption of CloudThink as the standard method for projecting physical vehicles into the cloud. The application space initially consists of a few fundamental and important applications (vehicle tethering and remote diagnostics, road-safety monitoring, and fuel economy analysis) but as CloudThink begins to gain widespread adoption, the multiplexing of applications on the same data structure and set will accelerate its adoption.

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“…A vehicle control with four-wheel-distributed steering and four-wheel-distributed traction/braking systems was proposed by Ono et al (2006). A strategy with throttle control and automatic transmission was proposed by Kim et al (2007). A yaw stability control system in which an active torque distribution and differential braking systems are used was put forward by Zhang et al (2009).…”

Section: Introductionmentioning

confidence: 99%

Nonlinear analysis of vehicle control actuations based on controlled invariant sets

Németh

Gáspár

Péni

2016

International Journal of Applied Mathematics and Computer Science

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In the paper, an analysis method is applied to the lateral stabilization problem of vehicle systems. The aim is to find the largest state-space region in which the lateral stability of the vehicle can be guaranteed by the peak-bounded control input. In the analysis, the nonlinear polynomial sum-of-squares programming method is applied. A practical computation technique is developed to calculate the maximum controlled invariant set of the system. The method calculates the maximum controlled invariant sets of the steering and braking control systems at various velocities and road conditions. Illustration examples show that, depending on the environments, different vehicle dynamic regions can be reached and stabilized by these controllers. The results can be applied to the theoretical basis of their interventions into the vehicle control system.

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Control of Integrated Powertrain With Electronic Throttle and Automatic Transmission

Cited by 112 publications

References 8 publications

CommonRoad: Composable benchmarks for motion planning on roads

CommonRoad: Composable benchmarks for motion planning on roads

Cloudthink: A Scalable Secure Platform for Mirroring Transportation Systems in the Cloud

Nonlinear analysis of vehicle control actuations based on controlled invariant sets

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