A Predictive Supervisory Controller for an HEV Operating in a Zero Emission Zone

Biswas, Dhrupad; Ghosh, Susenjit; Sengupta, Somnath; Mukhopadhyay, Siddhartha

doi:10.1109/itec.2019.8790631

Cited by 10 publications

(5 citation statements)

References 16 publications

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“…Therefore, conservative setpoints for SOC and tailpipe NO x must be chosen to maximize the probability that the SOC and NO x constraints are not violated. Contrary to earlier work [8,9], the studied case with ZE zone introduces an intermediate SOC constraint at t ZEZ (5) and tailpipe NO x emissions for the different work-based windows (6). This is illustrated in Figure 7.…”

Section: Studied Supervisory Controllersmentioning

confidence: 95%

“…In addition, two constraints are introduced. First, the battery energy at the entrance of ZE zone E b (t ZEZ ) has to be sufficient for full electric driving in the complete ZE zone, as described by (5). Note that not meeting this constraint means that the vehicle will strand, which is unacceptable.…”

Section: Optimal Control Problemmentioning

confidence: 99%

“…Although there are many studies around optimal control of hybrids using these methods, there is a very limited amount of literature in the application towards PHEV encountering ZE zones. Biswas et al [5], and Capancioni, et al [6], and Soldo et al [7], have proposed adaptive ECMS methods for this application. These methods center around coupling the mode of operation with the State-of-Charge (SOC) trajectory for the battery based on predicted information.…”

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confidence: 99%

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Towards Self-Learning Energy Management for Optimal PHEV Operation Around Zero Emission Zones

Kupper¹,

Mentink²,

Avramis³

et al. 2022

SAE Technical Paper Series

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Section: Studied Supervisory Controllersmentioning

confidence: 95%

Section: Optimal Control Problemmentioning

confidence: 99%

mentioning

confidence: 99%

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Towards Self-Learning Energy Management for Optimal PHEV Operation Around Zero Emission Zones

Kupper¹,

Mentink²,

Avramis³

et al. 2022

SAE Technical Paper Series

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“…In the open literature, green zone related research is dedicated to energy management for hybrid electric vehicles, see e.g. [16,17], and the impact on pollutant emissions is not considered in these studies. This is in line with the identified control challenges for hybrid electric vehicles in [18].…”

Section: Related Researchmentioning

confidence: 99%

Modeling and Control for Emission Management in Hybrid Electric Commercial Vehicles

Holmer

2022

Linköping Studies in Science and Technology. Dissertations

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Electrification of powertrains is a major trend in the vehicle industry. The reason behind this is mainly that electrification of a powertrain generally results in better fuel economy, by eliminating inefficient, low load, operation of the engine. This can be done in two ways: load shifting to shift the operation point of the engine to a more efficient one, or by turning off the engine completely. When it comes to emissions, load shifting generally have positive effect since it usually result in higher exhaust temperatures which are beneficial for the aftertreatment system. The effect from turning off the engine completely is more complicated. When the engine is turned off the aftertreatment system will start to cool down and will eventually lose its effectiveness, resulting in higher emissions when the engine is restarted. So-called green zones, zones established by legislation or demand of costumers, where the use of combustion engines is prohibited, are a good example of where this can be expected and is therefore a focus of this thesis. The applications are not limited to hybrids but also useful for all vehicles that make stops, e.g., commercial vehicles that make regulated 45 minutes breaks and loading/off-loading cargo.A model of a complete hybrid electric heavy-duty vehicle is developed and validated. The model is a compilation of several submodels of the different components in the vehicle. To correctly estimate the pollutive emissions, the components in the aftertreatment system are the most important components and emphasis is put on how the concentrations in them are calculated. It is shown that a quasi-static model for the concentrations gives the best balance in terms of accuracy and simulation time for the application. The aftertreatment system submodels are validated against data from a high-fidelity model and the complete powertrain is validated against experimental data from a powertrain in a test stand, all with satisfactory results. The model is used to create a virtual environment where the effect different control strategies have on the emissions around green zones can be studied and optimized.A control strategy based on pre-heating of the aftertreatment system is developed. The strategy heats the aftertreatment before turning off the engine in an optimal way to reduce NO x . This strategy is shown to be effective for engine-off times up to a few hours. However, for longer engine-off times, pre-heating of the aftertreatment system induces a limitation on the amount of stored ammonia, making the strategy ineffective or even bad. The strategy is extended to handle scenarios with multiple engine-off events using an algorithm that finds the engine-off events and handle them separately, but with a common equivalence factor between fuel and NO x to link them. The strategy is shown to handle scenarios with multiple engine-off events well, and the resulting distribution of fuel between the events is close to optimal. vii viii

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“…The Bike&Ride solution is very often supported by municipalities that set up a public system of bike rentals as part of a Bike-Sharing System (BSS) [69][70][71][72]; it is more and more often also supplemented by an Electric Scooter Sharing system [73,74]. Municipalities also actively engage in promoting public transport, e.g., via providing Free Fare Public Transport (FFPT) [75,76] and taking organisational measures to favour public transport, such as e.g., dedicated lanes for buses, trams, or light rail [77,78] or designating Low Emission Zones (LEZs) [79,80] and Zero Emission Zones (ZEZs) in city centres [81]. Research studies show that significant positive changes regarding environ-mental protection in urbanised areas may also be provided by ecodriving [82][83][84][85] as well as appropriate organisation and multimodal integration of passenger transport, including the special role to be played by rail transport [86,87].…”

Section: Literature Reviewmentioning

confidence: 99%

The Economic Effects of Electromobility in Sustainable Urban Public Transport

Pietrzak

2021

Energies

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This paper focuses on effects of implementing zero-emission buses in public transport fleets in urban areas in the context of electromobility assumptions. It fills the literature gap in the area of research on the impact of the energy mix of a given country on the issues raised in this article. The main purpose of this paper is to identify and analyse economic effects of implementing zero-emission buses in public transport in cities. The research area was the city of Szczecin, Poland. The research study was completed using the following research methods: literature review, document analysis (legal acts and internal documents), case study, ratio analysis, and comparative analysis of selected variants (investment variant and base variant). The conducted research study has shown that economic benefits resulting from implementing zero-emission buses in an urban transport fleet are limited by the current energy mix structure of the given country. An unfavourable energy mix may lead to increased emissions of SO2 and CO2 resulting from operation of this kind of vehicle. Therefore, achieving full effects in the field of electromobility in the given country depends on taking concurrent actions in order to diversify the power generation sources, and in particular on increasing the share of Renewable Energy Sources (RES).

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A Predictive Supervisory Controller for an HEV Operating in a Zero Emission Zone

Cited by 10 publications

References 16 publications

Towards Self-Learning Energy Management for Optimal PHEV Operation Around Zero Emission Zones

Towards Self-Learning Energy Management for Optimal PHEV Operation Around Zero Emission Zones

Modeling and Control for Emission Management in Hybrid Electric Commercial Vehicles

The Economic Effects of Electromobility in Sustainable Urban Public Transport

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