CONCEPT EVALUATION AND DEVELOPMENT OF A NOVEL APPROACH FOR INTEGRATION OF TURBOGENERATION, ELECTRIFICATION AND SUPERCHARGING ON HEAVY DUTY ENGINES

While many technologies such as electrically assisted turbocharging, exhaust energy recovery and mild hybridization have already proven to significantly increase heavy-duty engine efficiency, the key challenge to their widespread adoption has been their cost effectiveness and packaging. This research specifically addresses these challenges through evaluation and development of a novel technology concept termed as the Integrated Turbogeneration, Electrification and Supercharging (ITES) system. The concept integrates a secondary compressor, a turbocompound/expander turbine and an electric motor through a planetary gearset into the engine cranktrain. The approach enables a reduced system cost and space-claim, while maximizing the efficiency benefits of independent technologies. First, an assessment of design alternatives for integration of the identified key engine technologies on a heavy-duty engine was conducted. Once the ITES concept was down selected, the research then focused on model-based optimization and evaluation of the ITES system for a downsized medium heavy-duty diesel engine applied in Class 6-7 urban vocational application. As an outcome of the evaluation, a 1D simulation based sizing methodology of ITES system components was proposed. Furthermore, a novel control strategy for the ITES system was developed that combines equivalent consumption based steady-state offline optimization with functional controls for transient operation and smooth mode switching. The offline optimization method was also extended to evaluate the potential of ITES system in increasing aftertreatment temperature, which is critical for meeting future ultra-low NOx emission standards. Lastly, using 1D simulation of validated models, the efficiency benefit of ITES system on engine certification and vehicle drive cycles was predicted for the Class 6-7 urban vocational application. In comparison to baseline engine, the downsized engine with ITES system predicted an 8.5% reduction in engine fuel consumption on HDFTP cycle, 19.3% increase in fuel economy on ARB Transient cycle and 23.7% increase in fuel economy on a real-world drive cycle

Design of hybrid-electric aircraft with fault-tolerance considerations

The potential benefits of hybrid-electric or all-electric propulsion have led to a growing interest in this topic over the past decade. Preliminary design of propulsion systems and innovative configurations has been extensively discussed in literature, but steps towards higher levels of technological readiness, optimisation algorithms based on reliable weight estimation and simulation-based mission analysis are required. This paper focuses on the integration of a method for evaluating the lateral-directional controllability of an aircraft within a design chain that integrates aero-propulsive interactions, accurate modelling of the fuel system, and mid-fidelity estimation of the structural weight. Furthermore, the present work proposes a strategy for powerplant management in scenarios with an inoperative chain element. Benefits of hybrid-electric propulsion on the design of the vertical tail plane are evaluated involving the analysis of multiple failure scenarios and certification requirements. The proposed application concerns a commuter aircraft

Powertrain Systems for Net-Zero Transport

The transport sector continues to shift towards alternative powertrains, particularly with the UK Government’s announcement to end the sale of petrol and diesel passenger cars by 2030 and increasing support for alternatives. Despite this announcement, the internal combustion continues to play a significant role both in the passenger car market through the use of hybrids and sustainable low carbon fuels, as well as a key role in other sectors such as heavy-duty vehicles and off-highway applications across the globe. Building on the industry-leading IC Engines conference, the 2021 Powertrain Systems for Net-Zero Transport conference (7-8 December 2021, London, UK) focussed on the internal combustion engine’s role in Net-Zero transport as well as covered developments in the wide range of propulsion systems available (electric, fuel cell, sustainable fuels etc) and their associated powertrains. To achieve the net-zero transport across the globe, the life-cycle analysis of future powertrain and energy was also discussed. Powertrain Systems for Net-Zero Transport provided a forum for engine, fuels, e-machine, fuel cell and powertrain experts to look closely at developments in powertrain technology required, to meet the demands of the net-zero future and global competition in all sectors of the road transportation, off-highway and stationary power industries

COMPARATIVE ANALYSIS OF EFFICIENCY AND OPERATING CHARACTERISTICS OF AUTOMOTIVE POWERTRAIN ARCHITECTURES THROUGH CHASSIS DYNAMOMETER TESTING

The thesis COMPARATIVE ANALYSIS OF EFFICIENCY AND OPERATING CHARACTERISTICS OF AUTOMOTIVE POWERTRAIN ARCHITECTURES THROUGH CHASSIS DYNAMOMETER TESTING was completed through a collaborative partnership between Michigan Technological University and Argonne National Laboratory under a contractual agreement titled Advanced Vehicle Characterization at Argonne National Laboratory . The goal of this project was to investigate, understand and document the performance and operational strategy of several modern passenger vehicles of various architectures. The vehicles were chosen to represent several popular engine and transmission architectures and were instrumented to allow for data collection to facilitate comparative analysis. In order to ensure repeatability and reliability during testing, each vehicle was tested over a series of identical drive cycles in a controlled environment utilizing a vehicle chassis dynamometer. Where possible, instrumentation was preserved between vehicles to ensure robust data collection. The efficiency and fuel economy performance of the vehicles was studied. In addition, the powertrain utilization strategies, significant energy loss sources, tailpipe emissions, combustion characteristics, and cold start behavior were also explored in detail. It was concluded that each vehicle realizes different strengths and suffers from different limitations in the course of their attempts to maximize efficiency and fuel economy. In addition, it was observed that each vehicle regardless of architecture exhibits significant energy losses and difficulties in cold start operation that can be further improved with advancing technology. It is clear that advanced engine technologies and driveline technologies are complimentary aspects of vehicle design that must be utilized together for best efficiency improvements. Finally, it was concluded that advanced technology vehicles do not come without associated cost; the complexity of the powertrains and lifecycle costs must be considered to understand the full impact of advanced vehicle technology

Self-Learning Neural controller for Hybrid Power Management using Neuro-Dynamic Programming

A supervisory controller strategy for a hybrid vehicle coordinates the operation of the two power sources onboard of a vehicle to maximize objectives like fuel economy. In the past, various control strategies have been developed using heuristics as well as optimal control theory. The Stochastic Dynamic Programming (SDP) has been previously applied to determine implementable optimal control policies for discrete time dynamic systems whose states evolve according to given transition probabilities. However, the approach is constrained by the curse of dimensionality, i.e. an exponential increase in computational effort with increase in system state space, faced by dynamic programming based algorithms. This paper proposes a novel approach capable of overcoming the curse of dimensionality and solving policy optimization for a system with very large design state space. We propose developing a supervisory controller for hybrid vehicles based on the principles of reinforcement learning and neuro-dynamic programming, whereby the cost-to-go function is approximated using a neural network. The controller learns and improves its performance over time. The simulation results obtained for a series hydraulic hybrid vehicle over a driving schedule demonstrate the effectiveness of the proposed technique.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/89874/1/draft_01.pd

Powertrain Systems for Net-Zero Transport

The transport sector continues to shift towards alternative powertrains, particularly with the UK Government’s announcement to end the sale of petrol and diesel passenger cars by 2030 and increasing support for alternatives. Despite this announcement, the internal combustion continues to play a significant role both in the passenger car market through the use of hybrids and sustainable low carbon fuels, as well as a key role in other sectors such as heavy-duty vehicles and off-highway applications across the globe. Building on the industry-leading IC Engines conference, the 2021 Powertrain Systems for Net-Zero Transport conference (7-8 December 2021, London, UK) focussed on the internal combustion engine’s role in Net-Zero transport as well as covered developments in the wide range of propulsion systems available (electric, fuel cell, sustainable fuels etc) and their associated powertrains. To achieve the net-zero transport across the globe, the life-cycle analysis of future powertrain and energy was also discussed. Powertrain Systems for Net-Zero Transport provided a forum for engine, fuels, e-machine, fuel cell and powertrain experts to look closely at developments in powertrain technology required, to meet the demands of the net-zero future and global competition in all sectors of the road transportation, off-highway and stationary power industries

Electrified Powertrains for a Sustainable Mobility: Topologies, Design and Integrated Energy Management Strategies

This Special Issue was intended to contribute to the sustainable mobility agenda through enhanced scientific and multi-disciplinary knowledge to investigate concerns and real possibilities in the achievement of a greener mobility and to support the debate between industry and academic researchers, providing an interesting overview on new needs and investigation topics required for future developments

A Study on the Integration of a High-Speed Flywheel as an Energy Storage Device in Hybrid Vehicles

The last couple of decades have seen the rise of the hybrid electric vehicle as a compromise between the outstanding specific energy of petrol fuels and its low-cost technology, and the zero tail-gate emissions of the electric vehicle. Despite this, considerable reductions in cost and further increases in fuel economy are needed for their widespread adoption. An alternative low-cost energy storage technology for vehicles is the high-speed flywheel. The flywheel has important limitations that exclude it from being used as a primary energy source for vehicles, but its power characteristics and low-cost materials make it a powerful complement to a vehicle's primary propulsion system. This thesis presents an analysis on the integration of a high-speed flywheel for use as a secondary energy storage device in hybrid vehicles. Unlike other energy storage technologies, the energy content of the flywheel has a direct impact on the velocity of transmission. This presents an important challenge, as it means that the flywheel must be able to rotate at a speed independent of the vehicle's velocity and therefore it must be coupled via a variable speed transmission. This thesis presents some practical ways in which to accomplish this in conventional road vehicles, namely with the use of a variator, a planetary gear set or with the use of a power-split continuously variable transmission. Fundamental analyses on the kinematic behaviour of these transmissions particularly as they pertain to flywheel powertrains are presented. Computer simulations were carried out to compare the performance of various transmissions, and the models developed are presented as well. Finally the thesis also contains an investigation on the driving and road conditions that have the most beneficial effect on hybrid vehicle performance, with a particular emphasis on the effect that the road topography has on fuel economy and the significance of this

Supervisory Control Optimization for a Series Hybrid Electric Vehicle with Consideration of Battery Thermal Management and Aging

This dissertation integrates battery thermal management and aging into the supervisory control optimization for a heavy-duty series hybrid electric vehicle (HEV). The framework for multi-objective optimization relies on novel implementation of the Dynamic Programing algorithm, and predictive models of critical phenomena. Electrochemistry based battery aging model is integrated into the framework to assesses the battery aging rate by considering instantaneous lithium ion (Li+) surface concentration rather than average concentration. This creates a large state-action space. Therefore, the computational effort required to solve a Deterministic or Stochastic Dynamic Programming becomes prohibitively intense, and a neuro-dynamic programming approach is proposed to remove the ‘curse of dimensionality’ in classical dynamic programming. First, unified simulation framework is developed for in-depth studies of series HEV system. The integration of a refrigerant system model enables prediction of energy use for cooling the battery pack. Side reaction, electrolyte decomposition, is considered as the main aging mechanism of LiFePO4/Graphite battery, and an electrochemical model is integrated to predict side reaction rate and the resulting fading of capacity and power. An approximate analytical solution is used to solve the partial difference equations (PDEs) for Li+ diffusion. Comparing with finite difference method, it largely reduces the number of states with only a slight penalty on prediction accuracy. This improves computational efficiency, and enables inclusion of the electrochemistry based aging model in the power management optimization framework. Next, a stochastic dynamic programming (SDP) approach is applied to the optimization of supervisory control. Auxiliary cooling power is included in addition to vehicle propulsion. Two objectives, fuel economy and battery life, are optimized by weighted sum method. To reduce the computation load, a simplified battery aging model coupled with equivalent circuit model is used in SDP optimization; Li+ diffusion dynamics are disregarded, and surface concentration is represented by the average concentration. This reduces the system state number to four with two control inputs. A real-time implementable strategy is generated and embedded into the supervisory controller. The result shows that SDP strategy can improve fuel economy and battery life simultaneously, comparing with Thermostatic SOC strategy. Further, the tradeoff between fuel consumption and active Li+ loss is studied under different battery temperature. Finally, the accuracy of battery aging model for optimization is improved by adding Li+ diffusion dynamics. This increases the number of states and brings challenges to classical dynamic programming algorithms. Hence, a neuro-dynamic programming (NDP) approach is proposed for the problem with large state-action space. It combines the idea of functional approximation and temporal difference learning with dynamic programming; in that case the computation load increases linearly with the number of parameters in the approximate function, rather than exponentially with state space. The result shows that ability of NDP to solve the complex control optimization problem reliably and efficiently. The battery-aging conscientious strategy generated by NDP optimization framework further improves battery life by 3.8% without penalty on fuel economy, compared to SDP strategy. Improvements of battery life compared to the heuristic strategy are much larger, on the order of 65%. This leads to progressively larger fuel economy gains over time

The effectiveness of energy storage in hybrid vehicles

Public awareness of finite oil resources and concerns over climate change have spurred efforts to improve vehicle efficiency and reduce emissions by road transport. Hybrids have become an increasingly popular alternative to conventional powertrain vehicles. Large fuel savings are claimed (typically 70 + mpg) (Toyota, 2014), however, collective anecdotal evidence from owners of these vehicles suggests a more modest performance. A literature review yielded an abundance of literature relating to specific hybrid vehicle technologies, and control strategies, however the variation in energy savings over different journey types for different classes of vehicle has received less attention. A simulation tool was developed to compare the energy saving effectiveness of parallel hybrid powertrains with regenerative braking and energy storage across a broad range of vehicle and journey types. The realism of the simulation (in non-hybrid mode) was evaluated by comparison with practical trials. A range of validation methods showed that average fuel consumption could be calculated to within +/- 5-10% of measured consumption and, in cases where detailed data for a vehicle was available, this improved to within 3%. Simulated fuel consumption was around 15% greater that manufacturers’ claims – reasons for this were explored. Using the backward and forward looking simulation it was possible to calculate likely fuel savings in various scenarios. Results indicate a trend of improved potential savings with increased vehicle mass. Over urban journeys results ranged from around 16 to 23% energy savings for a small car and large coach respectively. On extra-urban journeys much more modest savings were calculated ranging from a maximum of 0 - 4 % across the same range of vehicles. The likely effects of vehicle mass and drag coefficient has also been explored along with the energy saving potential of start-stop engine technology, often used in hybrids and non-hybrids alike. The broad part of the study confirmed quantitatively that greatest fuel savings might be achieved on urban routes with public transport buses. The study then narrowed to consider this application, particularly with respect to exhaust emissions which are cause for growing concern. Possible reductions in exhaust NOx and PM emissions of up to 10 to 12% respectively were predicted through the application of parallel hybrid powertrains to existing bus designs and simulated on the MLTB cycle