Driving cycle characterization and generation, for design and control of fuel cell buses

Tazelaar, Edwin; Bruinsma, J.; Veenhuizen, P.A.; Bosch, P.P.J. van den

doi:10.3390/wevj3040812

Cited by 30 publications

(18 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…1) Data Preprocessing: Before using the real-world driving data for driving cycle synthesis, in several works, the data are preprocessed. A first way to do this is by segmenting the velocity values into different classes [10], [13]. For instance, all velocities can be segmented into discrete velocity classes, referred to also bins, with a constant bin width.…”

Section: Existing Driving Cycle Synthesis Methodsmentioning

confidence: 99%

“…Step 1: preprocessing of input (measured) cycles, i.e., segmentation into micro rips [11], [12]; Step 2: synthesis of a new driving cycle by using rule-based [9] or using Markov Chains [10]- [13], [15];…”

Section: Existing Driving Cycle Synthesis Methodsmentioning

confidence: 99%

“…In recent years, to improve the quality of the synthesized cycle speed, other methods have been proposed [10]- [12]. In addition to matching the driving cycle statistics, these include the random nature of a driving cycle as well.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Synthesis of Realistic Driving Cycles With High Accuracy and Computational Speed, Including Slope Information

Silvas

Hereijgers

Peng

et al. 2016

IEEE Trans. Veh. Technol.

View full text Add to dashboard Cite

This paper describes a new method to synthesize driving cycles, where not only the velocity is considered but the road slope information of the real-world measured driving cycle as well. Driven by strict emission regulations and tight fuel targets, hybrid or electric vehicle manufacturers aim to develop new and more energy-and cost-efficient powertrains. To enable and facilitate this development, short, yet realistic, driving cycles need to be synthesized. The developed driving cycle should give a good representation of measured driving cycles in terms of velocity, slope, acceleration, and so on. Current methods use only velocity and acceleration and assume a zero road slope. The heavier the vehicle is, the more important the road slope becomes in powertrain prototyping (as with component sizing or control design); hence, neglecting it leads to unrealistic or limited designs. To include the slope, we extend existing methods and propose an approach based on multidimensional Markov chains. The validation of the synthesized driving cycle is based on a statistical analysis (as the average acceleration or maximum velocity) and a frequency analysis. This new method demonstrates the ability of capturing the measured road slope information in the synthesized driving cycle. Furthermore, results show that the proposed method outperforms current methods in terms of accuracy and speed.Index Terms-Driving cycle compression, hybrid electric vehicle (HEV) design, multidimensional Markov chains, slope and velocity synthesis.

show abstract

Section: Existing Driving Cycle Synthesis Methodsmentioning

confidence: 99%

Section: Existing Driving Cycle Synthesis Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Synthesis of Realistic Driving Cycles With High Accuracy and Computational Speed, Including Slope Information

Silvas

Hereijgers

Peng

et al. 2016

IEEE Trans. Veh. Technol.

View full text Add to dashboard Cite

show abstract

“…By using only a single driving cycle when designing a vehicle there is a considerable risk that the vehicle is optimized for this specific driving cycle and the resulting design may be non-robust and have sub-optimal performance for other driving cycles (Tazelaar et al, 2009;Schwarzer and Ghorbani, 2013). The vehicle manufacturers need then only to focus on limited operating regions of the engine (Pelkmans and Debal, 2006) and since other driving cycles may excite different regions of the engine, different exhaust gas emissions and fuel consumption characteristics are obtained.…”

Section: Populärvetenskaplig Sammanfattningmentioning

confidence: 99%

Evaluation, Generation, and Transformation of Driving Cycles

Nyberg

2015

Linköping Studies in Science and Technology. Dissertations

View full text Add to dashboard Cite

Driving cycles are important components for evaluation and design of vehicles. They determine the focus of vehicle manufacturers, and indirectly they affect the environmental impact of vehicles since the vehicle control system is usually tuned to one or several driving cycles. Thus, the driving cycle affects the design of the vehicle since cost, fuel consumption, and emissions all depend on the driving cycle used for design. Since the existing standard driving cycles cannot keep up with the changing road infrastructure, the changing vehicle fleet composition, and the growing number of vehicles on the road, which do all cause changes in the driver behavior, the need to get new and representative driving cycles are increasing. A research question is how to generate these new driving cycles so that they are both representative and at the same time have certain equivalence properties, to make fair comparisons of the performance results. Besides generation, another possibility to get more driving cycles is to transform the existing ones into new, different, driving cycles considering equivalence constraints.With the development of new powertrain concepts the need for evaluation will increase, and an interesting question is how to utilize new developments in dynamometer technology together with new possibilities for connecting equipment. Here a pedal robot is developed to be used in a vehicle mounted in a chassis dynamometer and the setup is used for co-simulation together with a moving base simulator that is connected with a communication line. The results show that the co-simulation can become a realistic driving experience and a viable option for dangerous tests and a complement to tests on a dedicated track or on-road tests, if improvements on the braking and the vehicle feedback to the driver are implemented.The problem of generating representative driving cycles, with specified excitation at the wheels, is approached with a combined two-step method. A Markov chain approach is used to generate candidate driving cycles that are then transformed to equivalent driving cycles with respect to the mean tractive force components, which are the used measures. Using an optimization methodology the transformation of driving cycles is formulated as a nonlinear program with constraints and a cost function to minimize. The nonlinear program formulation can handle a wide range of constraints, e.g., the mean tractive force components, different power measures, or available energy for recuperation, and using the vehicle jerk as cost function gives good drivability.In conclusion, methods for driving cycle design have been proposed where new driving cycles can either be generated from databases, or given driving cycles can be transformed to fulfill certain equivalence constraints, approaching the important problem of similar but not the same. The combination of these approaches yields a stochastic and general method to generate driving cycles with equivalence properties that can be used at several instances during the prod...

show abstract

“…Therefore driving cycles play a fundamental role in the design of vehicles, and if vehicle manufacturers focus only on a single driving cycle, during the development and design of a vehicle, there is a risk that the design is optimized for this specific driving cycle and the result for another driving cycle may be non-robust and sub-optimal [4], [5].…”

Section: Introductionmentioning

confidence: 99%

Driving Cycle Equivalence and Transformation

Nyberg

Frisk

Nielsen

2017

IEEE Trans. Veh. Technol.

View full text Add to dashboard Cite

Abstract-There is a current strong trend where driving cycles are used extensively in vehicle design, especially for calibration and tuning of all powertrain systems for control and diagnosis. In such situations it is essential to capture real driving, and therefore using only a few driving cycles would lead to the risk that a test or a design would be tailored to details in a specific driving cycle. Consequently there are now widespread activities using techniques from statistics, big data and mission modeling to address these issues. For all such methods there is an important final step to calibrate a representative cycle to adhere to fair propulsion requirements on the driven wheels over a cycle. For this a general methodology has been developed, applicable to a wide range of problems involving driving cycle transformations. It is based on a definition of equivalence for driving cycles that loosely speaking defines being similar without being the same. Based on this, a set of algorithms are developed to transform a given driving cycle into an equivalent one, or into a cycle with given equivalence measure. The transformations are effectively handled as a nonlinear program that is solved using general purpose optimization techniques. The proposed method is general and a wide range of constraints can be used.

show abstract

Driving cycle characterization and generation, for design and control of fuel cell buses

Cited by 30 publications

References 10 publications

Synthesis of Realistic Driving Cycles With High Accuracy and Computational Speed, Including Slope Information

Synthesis of Realistic Driving Cycles With High Accuracy and Computational Speed, Including Slope Information

Evaluation, Generation, and Transformation of Driving Cycles

Driving Cycle Equivalence and Transformation

Contact Info

Product

Resources

About