Abstract

Road transport is responsible for a significant share of the global GHG emissions. In order to address the increasing trend of road vehicle emissions, due to its heavy reliance on oil, Nordic countries have set ambitious goals and policies for the reduction of road transport GHG emissions. Despite the fact that the latest developments in the passenger car segment are leading towards the progressive electrification of the fleet, the decarbonization of heavy-duty vehicle segment presents significant challenges that are yet to be overcome. This study focuses, on the first part, on the regulatory framework of fuel economy standards of road vehicles, highlighting the absence of a European regulation on fuel efficiency for the heavy-duty sector. Energy efficiency technologies can be grouped mainly in vehicle technologies, driveline and powertrain technologies, and alternative fuels. The fuel efficiency of HDVs can be positively improved at different vehicle levels, but the technology benefit and its economic feasibility are heavily dependent on the vehicle type and the operational cycle considered. The electrification pathway has the potential of reducing the carbon emission to a great extent, but the current battery technologies have proven to be not cost efficient for the heavy vehicles, because of the high purchase price and the low range, related to the battery cost and inferior energy density compared to conventional liquid fuels.   A scenario development model has been created in order to estimate and quantify the impact of future developments and emission reduction measures in Finland, Sweden and Norway for the timeframe 2016-2050, with a focus on 2030 results. Two scenarios concerning the powertrain developments of heavy-duty vehicles and buses have been created, a conservative scenario and electric scenario, as well as vehicle efficiency improvements and fuel consumption scenarios. Additional sets of parameters have been estimated as input for the model, such as national transport need and load assumptions. The results highlight the challenges of achieving the national GHG emission reduction targets with the current measures in all three countries. The slow fleet renewal rates and the high forecasted increase of transport need limit the benefits of alternative and more efficient powertrains introduced in the fleet by new vehicles. The heavy-duty transport is expected to maintain its heavy reliance on diesel fuel and hinder the improvements of the light-duty segments. A holistic approach is needed to reduce the GHG emissions from road transport, including more efficient powertrains, higher biofuel shares and progressive electrification.

Abstract

The operation of heavy-duty vehicles at small inter-vehicular distances, known as platoons, lowers the aerodynamic drag and, therefore, reduces fuel consumption and greenhouse gas emissions. Tests conducted on flat roads have shown the potential of platooning to reduce the fuel consumption of about 10%. However, platoons are expected to operate on public highways with varying topography alongside other vehicles. Due to the large mass and limited engine power of heavy-duty vehicles, road slopes have a significant impact on feasible and optimal speed profiles. For single vehicles, experiments have shown that optimizing the speed according to the road profile resulted in fuel saving of up to 3.5%. The use of such a look-ahead control framework is expected to lead to large benefits also for platooning. This thesis presents the design of safe and fuel-efficient control of heavy-duty vehicle platoons driving on realistic road profiles. The scenario where the platooning vehicles cooperate to optimize their overall fuel-efficiency is studied together with the scenario where the vehicles do not explicitly cooperate. First, we propose a control architecture that splits the cooperative platooning control problem into two layers. The top layer computes a reference speed profile that ensures fuel-efficient operation of the entire platoon based on dynamic programming. The bottom layer relies on model predictive control to safely track the reference speed. Simulations show the ability of the proposed controller to save up to 12% of fuel for following vehicles compared to existing platoon controllers and to safely react to emergency braking of the leading vehicle. Second, we propose a gear management layer that fits in the cooperative platooning control architecture and explicitly takes the gear selection into account. The underlying optimal control problem aims at minimizing the vehicle fuel consumption and the reference tracking deviations. Simulations indicate how this formulation outperforms existing alternatives, both in terms of fuel-efficiency and tracking error. Third, we address non-cooperative platooning by proposing a vehicle-following controller suitable for fuel-efficient control of heavy-duty vehicles. The proposed controller explores both the benefits given by the short inter-vehicular distance and those given by pulse-and-glide, i.e., alternating traction and coasting phases. A simulation study suggests fuel saving of up to 18% compared to the single vehicle case, and up to 7% compared to when a constant-distance vehicle-following controller is used. Last, we propose a vehicle-following controller aimed at exploiting long preview of the preceding vehicle trajectory by directly manipulating the inputs of low-level vehicle controllers. This is achieved through a model predictive controller that uses a short prediction horizon and includes a terminal state set that incorporates preview information about the preceding vehicle. Experiments indicate the ability of the controller to avoid unnecessary braking, while simulations show behavior similar to the optimal control behavior. "p"QC 20180416

Abstract

On-road vehicle emissions are one of the major sources of transport emissions. As a key design factor, road grades (or road slopes) have significant effects on on-road vehicle emissions, particularly on Heavy-Duty Vehicles (HDVs). However, the research into the relationship between road grades and on-road vehicle emissions is very rare in China. Taking a road network in Taiyuan, China, as a study area, this paper explored the influences of road grades on carbon monoxide (CO), hydrocarbon (HC), and nitrogen oxide (NOx) emissions of HDVs. Combining emissions data collected by Portable Emission Measurement System (PEMS) with Vehicle Specific Power (VSP), we developed an emission rate model of HDVs. Then, we integrated it with the traffic simulation model VISSIM to attain the emissions of HDVs on nine scenarios differentiated by road grades. The results showed that the three emissions are found to be highly correlated to road grades, among which the CO emissions are most sensitive to the change of road grades and the HC emissions least. Compared to the emissions at 0% grade, the emissions at 4% grade will be boosted from 39.0% to 60.6%. The CO and NOx emissions increase with the road grades in all nine scenarios, while the variations of HC emissions in different scenarios were complicated. The findings of this research will provide insights for policy-makers, scholars, and practitioners into strategies for improving road design to reduce traffic emissions and develop sustainable transportation in China. Document type: Article