CERES :: Browsing by Author "Assadian, Francis"

Browsing by Author "Assadian, Francis"

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Open Access
Comparative analysis of forward-facing models vs backward-facing models in powertrain component sizing
(Institution of Engineering and Technology, 2013-11-11) Mohan, Ganesh; Assadian, Francis; Longo, Stefano
Powertrain size optimisation based on vehicle class and usage profile is advantageous for reducing emissions. Backward-facing powertrain models, which incorporate scalable powertrain components, have often been used for this purpose. However, due to their quasi-static nature, backward-facing models give very limited information about the limits of the system and drivability of the vehicle. This makes it difficult for control system development and implementation in hardware-in-the-loop (HIL) test systems. This paper investigates the viability of using forward-facing models in the context of powertrain component sizing optimisation. The vehicle model used in this investigation features a conventional powertrain with an internal combustion engine, clutch, manual transmission, and final drive. Simulations that were carried out have indicated that there is minimal effect on the optimal cost with regards to variations in the driver model sensitivity. This opens up the possibility of using forward-facing models for the purpose of powertrain component sizing.
Open Access
A Conjugate Gradient-Based BPTT-Like Optimal Control Algorithm With Vehicle Dynamics Control Application
(Institute of Electrical and Electronics Engineers, 2010-11-01T00:00:00Z) Kasac, Josip; Deur, Josko; Novakovic, Branko; Kolmanovsky, Ilya V.; Assadian, Francis
The paper presents a gradient-based algorithm for optimal control of nonlinear multivariable systems with control and state vectors constraints. The algorithm has a backward-in-time recurrent structure similar to the backpropagation-through-time algorithm, which is mostly used as a learning algorithm for dynamic neural networks. Other main features of the algorithm include the use of higher order Adams time-discretization schemes, numerical calculation of Jacobians, and advanced conjugate gradient methods for favorable convergence properties. The algorithm performance is illustrated on an example of off-line vehicle dynamics control optimization based on a realistic high-order vehicle model. The optimized control variables are active rear differential torque transfer and active rear steering road wheel angle, while the optimization tasks are trajectory tracking and roll minimization for a double lane change maneuver.
Open Access
Fast model predictive control and its application to energy management of hybrid electric vehicles
(Intechopen, 2011-06-24) Fekri, Sajjad; Assadian, Francis
Modern day automotive engineers are required, among other objectives, to maximize fuel economy and to sustain a reasonably responsive car (i.e. maintain driveability) while still meeting increasingly stringent emission constraints mandated by the government. Towards this end, Hybrid Electric Vehicles (HEVs) have been introduced which typically combine two different sources of power, the traditional internal combustion engine (ICE) with one (or more) electric motors, mainly for optimising fuel efficiency and reducing Carbon Dioxide (CO2) and greenhouse gases (GHG) (Fuhs, 2008).
Open Access
A Hardware-in-the-Loop Facility for Integrated Vehicle Dynamics Control System Design and Validation
(Elsevier, 2016-11-10) Soltani, Amirmasoud; Assadian, Francis
Due to the increased number and the complexity of the embedded systems in today’s vehicle, there is ever increasing pressure to reduce the development cost and time to market of such systems. In recent years, Model based Development (MBD) is becoming a main stream in the development of automotive embedded systems, and Hardware-in-the-Loop (HiL) testing is one of the key steps toward the implementation of MBD approach. This paper presents the recent HiL facility that has been developed at Cranfield University. The HiL setup includes real steering and brake smart actuator, high fidelity validated vehicle model, complete rapid control prototyping tool chain, and driver-in-the-loop capability. The applications of HiL setup are including but not limited to: smart actuators system identification; rapid control development and early validation of standalone and/or integrated vehicle dynamics control systems. Furthermore, the facility can be employed for investigation on driver-vehicle interaction at the presence of standalone active steering and/or brake systems as well as various Advanced Driver Assist Systems (ADAS), such as lane keeping or adaptive cruise control systems. The capability of the HiL facility for validation of a several newly developed vehicle dynamics control systems is presented
Open Access
Impact of battery ageing on an electric vehicle powertrain optimisation
(International Centre for Sustainable Development of Energy, Water and Environment Systems, 2014-12-01) Auger, Daniel J.; Groff, Maxime F.; Mohan, Ganesh; Longo, Stefano; Assadian, Francis
An electric vehicle’s battery is its most expensive component, and it cannot be charged and discharged indefinitely. This affects a consumer vehicle’s end-user value. Ageing is tolerated as an unwanted operational side-effect; manufacturers have little control over it. Recent publications have considered trade-offs between efficiency and ageing in plug-in hybrids (PHEVs) but there is no equivalent literature for pure EVs. For PHEVs, battery ageing has been modelled by translating current demands into chemical degradation. Given such models it is possible to produce similar trade-offs for EVs. We consider the effects of varying battery size and introducing a parallel supercapacitor pack. (Supercapacitors can smooth current demands, but their weight and electronics reduce economy.) We extend existing EV optimisation techniques to include battery ageing, illustrated with vehicle case studies. We comment on the applicability to similar EV problems and identify where additional research is needed to improve on our assumptions.
Open Access
Journey predictive energy management strategy for a plug-in hybrid electric vehicle
(Cranfield University, 2013-05) Dharmaraj Ram Manohar, Ravi Shankar; Marco, J.; Assadian, Francis
The adoption of Plug-in Hybrid Electric Vehicles (PHEVs) is widely seen as an interim solution for the decarbonisation of the transport sector. Within a PHEV, determining the required energy storage capacity of the battery remains one of the primary concerns for vehicle manufacturers and system integrators. This fact is particularly pertinent since the battery constitutes the largest contributor to vehicle mass. Furthermore, the financial cost associated with the procurement, design and integration of battery systems is often cited as one of the main barriers to vehicle commercialisation. The ability to integrate the optimization of the energy management control system with the sizing of key PHEV powertrain components presents a significant area of research. Further, recent studies suggest the use of \intelligent transport" infrastructure to include a predictive element to the energy management strategy to achieve reductions in emissions. The thesis addresses the problem of determining the links between component-sizing, real-world usage and energy management strategies for a PHEV. The objective is to develop an integrated framework in which the advantages of predictive energy management can be realised by component downsizing for a PHEV. The study is spilt into three sections. The first part presents the framework by which the predictive element can be included into the PHEV's energy management strategy. Second part describes the development of the PHEV component models and the various energy management strategies which control the split in energy used between the engine and the battery. In this section a new control strategy is presented which integrates the predictive element proposed in the first part. Finally, in the third section an optimisation framework is presented by which the size of the components within the PHEV are reduced due to the lower energy demands of the new proposed energy management strategy. The first part of the study presents a framework by which the energy consumption of a vehicle may be predicted over a route. The proposed energy prediction framework employs a neural network and was used o_-line for estimating the real-world energy consumption of the vehicle so that it can be later integrated within the vehicles energy management control system. Experimental results show an accuracy within 20%-30% when comparing predicted and measured energy consumptions for over 800 different real-world EV journeys … [cont.].
Open Access
Low cost integration of Electric Power-Assisted Steering (EPAS) with Enhanced Stability Program (ESP)
(Cranfield University, 2014-11) Soltani, Amirmasoud; Assadian, Francis
Vehicle Dynamics Control (VDC) systems (also known as Active Chassis systems) are mechatronic systems developed for improving vehicle comfort, handling and/or stability. Traditionally, most of these systems have been individually developed and manufactured by various suppliers and utilised by automotive manufacturers. These decentralised control systems usually improve one aspect of vehicle performance and in some cases even worsen some other features of the vehicle. Although the benefit of the stand-alone VDC systems has been proven, however, by increasing the number of the active systems in vehicles, the importance of controlling them in a coordinated and integrated manner to reduce the system complexity, eliminate the possible conflicts as well as expand the system operational envelope, has become predominant. The subject of Integrated Vehicle Dynamics Control (IVDC) for improving the overall vehicle performance in the existence of several VDC active systems has recently become the topic of many research and development activities in both academia and industries Several approaches have been proposed for integration of vehicle control systems, which range from the simple and obvious solution of networking the sensors, actuators and processors signals through different protocols like CAN or FlexRay, to some sort of complicated multi-layered, multi-variable control architectures. In fact, development of an integrated control system is a challenging multidisciplinary task and should be able to reduce the complexity, increase the flexibility and improve the overall performance of the vehicle. The aim of this thesis is to develop a low-cost control scheme for integration of Electric Power-Assisted Steering (EPAS) system with Enhanced Stability Program (ESP) system to improve driver comfort as well as vehicle safety. In this dissertation, a systematic approach toward a modular, flexible and reconfigurable control architecture for integrated vehicle dynamics control systems is proposed which can be implemented in real time environment with low computational cost. The proposed control architecture, so named “Integrated Vehicle Control System (IVCS)”, is customised for integration of EPAS and ESP control systems. IVCS architecture consists of three cascade control loops, including high-level vehicle control, low-level (steering torque and brake slip) control and smart actuator (EPAS and EHB) control systems. The controllers are designed based on Youla parameterisation (closed-loop shaping) method. A fast, adaptive and reconfigurable control allocation scheme is proposed to coordinate the control of EPAS and ESP systems. An integrated ESP & ESP HiL/RCP system including the real EPAS and Electro Hydraulic Brake (EHB) smart actuators integrated with a virtual vehicle model (using CarMaker/HiL®) with driver in the loop capability is designed and utilised as a rapid control development platform to verify and validate the developed control systems in real time environment. Integrated Vehicle Dynamic Control is one of the most promising and challenging research and development topics. A general architecture and control logic of the IVDC system based on a modular and reconfigurable control allocation scheme for redundant systems is presented in this research. The proposed fault tolerant configuration is applicable for not only integrated control of EPAS and ESP system but also for integration of other types of the vehicle active systems which could be the subject of future works.
Open Access
Mechatronics in Sustainable Mobility: Two Electric Vehicle Applications
(Greenleaf Publishers, 2014-05-01) Longo, Stefano; Auger, Daniel J.; Assadian, Francis
In this paper, we ﬁrst review the role that mechatronics and advanced control have in modern road vehicles, in particular their present and potential impact on sustainable mobility. We then illustrate this with two research examples. Firstly, we show how electronic science, control system techniques and computing manifest themselves in the design of an advanced battery management algorithm designed to estimate two unmeasurable but vital quantities, State of Charge (SoC) and State of Health (SoH): this allows better utilisation of battery capacity, with scope for advanced prognostics and diagnostics. Secondly, we show how multi-domain modelling integrating mechanical science and electronic science can be used to express component ageing as part of a set of vehicle-level performance objectives and used to explore the trade-offs between conﬂicting requirements, aiding sensible design choices.
Open Access
Multi-objective optimisation for battery electric vehicle powertrain topologies
(Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 2016-10-06) Othaganont, Pongpun; Assadian, Francis; Auger, Daniel J.
Electric vehicles are becoming more popular in the market. To be competitive, manufacturers need to produce vehicles with a low energy consumption, a good range and an acceptable driving performance. These are dependent on the choice of components and the topology in which they are used. In a conventional gasoline vehicle, the powertrain topology is constrained to a few well-understood layouts; these typically consist of a single engine driving one axle or both axles through a multi-ratio gearbox. With electric vehicles, there is more flexibility, and the design space is relatively unexplored. In this paper, we evaluate several different topologies as follows: a traditional topology using a single electric motor driving a single axle with a fixed gear ratio; a topology using separate motors for the front axle and the rear axle, each with its own fixed gear ratio; a topology using in-wheel motors on a single axle; a four-wheel-drive topology using in-wheel motors on both axes. Multi-objective optimisation techniques are used to find the optimal component sizing for a given requirement set and to investigate the trade-offs between the energy consumption, the powertrain cost and the acceleration performance. The paper concludes with a discussion of the relative merits of the different topologies and their applicability to real-world passenger cars.
Open Access
New slip control system considering actuator dynamics
(SAE International, 2015-04-14) Soltani, Amirmasoud; Assadian, Francis
A new control strategy for wheel slip control, considering the complete dynamics of the electro-hydraulic brake (EHB) system, is developed and experimentally validated in Cranfield University's HiL system. The control system is based on closed loop shaping Youla-parameterization method. The plant model is linearized about the nominal operating point, a Youla parameter is defined for all stabilizing feedback controller and control performance is achieved by employing closed loop shaping technique. The stability and performance of the controller are investigated in frequency and time domain, and verified by experiments using real EHB smart actuator fitted into the HiL system with driver in the loop.
Open Access
Optimal handling characteristics for electric vehicles with torque vectoring.
(2017-08) Smith, Edward N.; Cao, Dongpu; Velenis, Efstathios; McNally, Mark; Assadian, Francis
Torque vectoring by virtue of independent electric motors is the focus of an increasing number of studies as electric vehicles gain prominence as the chosen direction for the automotive industry. Building on active yaw control systems developed over the past decades, torque vectoring benefits from the high-responsiveness and controllability of the electric motor actuator. Furthermore, and especially in the case of vehicles equipped with one independent motor per wheel, the overall performance envelope of the vehicle is significantly improved, as well as the ability to actively shape the vehicle handling. Much attention has been focussed on controller development and control allocation aspects of torque vectoring controllers, but little on the appropriate yaw rate reference. Optimal control studies have been successfully used to mimic the expert driver in both minimum-time circuit racing and high-sideslip rally driving, and can offer insight into how to optimally tune active chassis control systems, such as torque vectoring yaw control. The main aim of this thesis was to investigate the optimal handling characteristics of an electric vehicle with four independent electric motors at the limits of performance. A TV controller was first developed for a prototype sportscar with 4 independent motors, employing a model-based design process that encompassed real-time software in the loop testing. Real-world track testing demonstrated the controller was able to successfully modify the handling characteristic of the vehicle in both understeer and oversteer directions, achieving good controller performance in steady-state and transient manoeuvres. The limit performance of the TV-controlled vehicle was subsequently investigated in the simulation domain. Numerical techniques were used to solve optimal control problems for a single-track vehicle model with linear tyres and an external yaw moment term representing the overall yaw moment arising from the difference in torques at each wheel. For a U-turn manoeuvre, it was shown that torque vectoring significantly lowers manoeuvre time in comparison with the vehicle without TV active, and that modifying the passive understeer gradient does not affect manoeuvre time. The system dynamics were reformulated to include a feedback torque vectoring controller. The target yaw rate reference was varied and it was found that the manoeuvre time was highly sensitive to the yaw rate reference. For minimising laptime, the target understeer gradient should be set to the passive understeer gradient value. The methodology was repeated for a higher fidelity model including nonlinear tyres and lateral load transfer, and found that when the torque vectoring controller was included in the system dynamics, the manoeuvre time showed little sensitivity to the target understeer gradient. Following the contradictory results of the optimal control problems, the vehicle models were investigated next. Time optimal yaw rate gain surfaces were generated from further minimum-time optimal control problems. Open-loop manoeuvres investigating effects of tyre model, lateral load transfer and torque vectoring generation mechanism found that tyre modelling was the dominant differentiator and tyre nonlinearity is an essential modelling consideration. Optimal control techniques have been used for high sideslip manoeuvring for conventional vehicles but no studies have explored the effects of torque vectoring on agility. In the final chapter, an aggressive turn-around manoeuvre was simulated and it was found that torque vectoring can significantly increase agility and reduce the space taken for an aggressive turn-around manoeuvre. Reducing yaw inertia increased agility, as well as increasing longitudinal slips limits. A critique of agility metrics in this context was given.
Open Access
Optimal time and handling methods for motorsport differentials.
(Cranfield University, 2014-12) Tremlett, Anthony; Assadian, Francis; Vaughan, Nicholas D.
In the motorsport environment, where traction at one wheel is often compromised due to high cornering accelerations, Limited Slip Differentials (LSD) offer significant improvements in traction and vehicle stability. LSDs achieve these performance benefits through the transfer of torque from the faster to slower rotating driving wheel. In the majority of racing formulae, modern devices have evolved to become highly adjustable, allowing this torque bias to alter both ultimate vehicle performance and handling balance through specific corner entry, apex and corner exit phases. This work investigates methods to optimise LSD setup parameters, both for minimum lap time and desirable handling characteristics. The first stage of addressing this objective involved the creation of a range of contemporary motorsport LSD models. These included a plate or Salisbury type, a Viscous Coupling (VC) and a Viscous Combined Plate (VCP). A differential test rig was developed to validate these models. The parameter optimisation is addressed in two main parts. Firstly, a Quasi Steady State (QSS) time optimal method is used to maximise the vehicle's GG acceleration envelope using a direct, nonlinear program (NLP). A limitation of this approach however, is that system transients are neglected. This is addressed through the development of an alternative indirect, nonlinear optimal control (NOC) method. Both methods were able to find LSD setup parameters which minimised lap time, providing significant improvements over traditional open and locked devices. The NOC method however, was able to give greater insight into how a locked device ultimately limits the vehicle yaw response during quick direction changes. The time optimal analysis was extended to investigate aspects of vehicle stability and agility. These factors are known to have a major influence on driveability and thus, how much of the theoretical performance limit the driver can extract. A more unified GG diagram framework was implemented, to characterise both the vehicle's acceleration limits, and how its stability and agility changes leading up to this limit. The work has generated a number of novel contributions in this research field. Firstly, the creation and validation of a range of state-of-the-art motorsport LSD models. Secondly, the methodologies used to optimise LSD setup parameters, the results from which, have themselves provided the basis of a novel, vehicle speed dependent LSD device. Finally, a more practical and intuitive way to evaluate vehicle stability and agility at different cornering phases. This has laid the foundations of a procedure which not only maximises the vehicle's acceleration limits, but also allows its response to be tailored to suit individual driver preferences.
Open Access
An Optimization Framework for Comparative Analysis of Multiple Vehicle Powertrains
(MDPI , 2013-10-22T00:00:00Z) Mohan, Ganesh; Assadian, Francis; Longo, Stefano
With a myriad of alternative vehicle powertrain architectures emerging in the industry, such as electric vehicles and hybrid electric vehicles, it is beneficial that the most appropriate system is chosen for the desired vehicle class and duty cycle, and to minimize a given cost function. This paper investigates this issue, by proposing a novel framework that evaluates different types of powertrain architectures under a unified modular powertrain structure. This framework provides a systematic and objective approach to comparing different types of powertrain architectures simultaneously, and will highlight the benefits that can be achieved from each architecture, thus making it possible to develop the reasoning for manufacturers to implement such systems, and potentially accelerate customer take-up of alternative powertrain technology. The results from this investigation have indicated that such analysis is indeed possible, by way of identifying the “cross-over point” between powertrain architectures, where one powertrain architecture transitions into a different architecture with increments in the required travel range.
Open Access
Sensitivity analyses for cross-coupled parameters in automotive powertrain optimization
(MDPI, 2014-06-17) Othaganont, Pongpun; Assadian, Francis; Auger, Daniel J.
When vehicle manufacturers are developing new hybrid and electric vehicles, modeling and simulation are frequently used to predict the performance of the new vehicles from an early stage in the product lifecycle. Typically, models are used to predict the range, performance and energy consumption of their future planned production vehicle; they also allow the designer to optimize a vehicle’s configuration. Another use for the models is in performing sensitivity analysis, which helps us understand which parameters have the most influence on model predictions and real-world behaviors. There are various techniques for sensitivity analysis, some are numerical, but the greatest insights are obtained analytically with sensitivity defined in terms of partial derivatives. Existing methods in the literature give us a useful, quantified measure of parameter sensitivity, a first-order effect, but they do not consider second-order effects. Second-order effects could give us additional insights: for example, a first order analysis might tell us that a limiting factor is the efficiency of the vehicle’s prime-mover; our new second order analysis will tell us how quickly the efficiency of the powertrain will become of greater significance. In this paper, we develop a method based on formal optimization mathematics for rapid second-order sensitivity analyses and illustrate these through a case study on a C-segment electric vehicle.
Open Access
A toolbox for multi-objective optimisation of low carbon powertrain topologies
(Cranfield University, 2016-05) Mohan, Ganesh; Assadian, Francis; Longo, Stefano
Stricter regulations and evolving environmental concerns have been exerting ever-increasing pressure on the automotive industry to produce low carbon vehicles that reduce emissions. As a result, increasing numbers of alternative powertrain architectures have been released into the marketplace to address this need. However, with a myriad of possible alternative powertrain configurations, which is the most appropriate type for a given vehicle class and duty cycle? To that end, comparative analyses of powertrain configurations have been widely carried out in literature; though such analyses only considered limited types of powertrain architectures at a time. Collating the results from these literature often produced findings that were discontinuous, which made it difficult for drawing conclusions when comparing multiple types of powertrains. The aim of this research is to propose a novel methodology that can be used by practitioners to improve the methods for comparative analyses of different types of powertrain architectures. Contrary to what has been done so far, the proposed methodology combines an optimisation algorithm with a Modular Powertrain Structure that facilitates the simultaneous approach to optimising multiple types of powertrain architectures. The contribution to science is two-folds; presenting a methodology to simultaneously select a powertrain architecture and optimise its component sizes for a given cost function, and demonstrating the use of multi-objective optimisation for identifying trade-offs between cost functions by powertrain architecture selection. Based on the results, the sizing of the powertrain components were influenced by the power and energy requirements of the drivecycle, whereas the powertrain architecture selection was mainly driven by the autonomy range requirements, vehicle mass constraints, CO2 emissions, and powertrain costs. For multi-objective optimisation, the creation of a 3-dimentional Pareto front showed multiple solution points for the different powertrain architectures, which was inherent from the ability of the methodology to concurrently evaluate those architectures. A diverging trend was observed on this front with the increase in the autonomy range, driven primarily by variation in powertrain cost per kilometre. Additionally, there appeared to be a trade-off in terms of electric powertrain sizing between CO2 emissions and lowest mass. This was more evident at lower autonomy ranges, where the battery efficiency was a deciding factor for CO2 emissions. The results have demonstrated the contribution of the proposed methodology in the area of multi-objective powertrain architecture optimisation, thus addressing the aims of this research.

Browsing by Author "Assadian, Francis"

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