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To introduce the programme and the courses and the facilities available at ³ÉÈËÖ±²¥.

• Team working
• Project management
• Various interpersonal skills: report writing and presentation skills 
• Various MS Office training packages
• Library sessions with the Information Team covering qualitative information, referencing, ethics and plagiarism.
• Careers sessions including CV writing, preparation for interviews and assessment centres, interview techniques.

On successful completion of this module you will:

• Have an appreciation of the Automotive Mechatronics Masters programme and course philosophy, structure, content, teaching methods, staff and administration.
• Be familiar with key facilities (internal and external to ³ÉÈËÖ±²¥) and resources such as the library, computer network and Careers Service.
• Have essential, fundamental knowledge prior to the study including a range of computing-related skills.
• Have experienced team building and other interpersonal skills including written and verbal communication skills.
• Appreciate the importance of time/project management throughout the study and Health and Safety at workplace.

This module will provide deep understanding of vehicle propulsion options and driveline supporting students to analyse and predict vehicle performance. The interdependency of vehicle systems will be reviewed to critically evaluate the integration of different alternative powertrain options and be able to select appropriate solutions within legislation framework.

Basic vehicle characteristics: Vehicle concepts, centre of gravity position, static and dynamic loads and weight distributions, front, rear and all wheel drive. Adhesion coefficient and influencing factors. Traction, braking and resistance to motion.

Fuel consumption: Engine characteristics & fuel maps. Determination of fuel consumption. Energy aspects. Legislative Drive Cycles.

Off-Road: Introduction to off road vehicle design characteristics.

Autonomy: Review of the current technologies surrounding Vehicle Autonomous Driving.

Braking performance: Influence of resistances and inertia. Brake force distribution. ECE 13 legislation. Calculation of required braking characteristics. Stopping distance.

Safety: Principles of passenger restraints, elastic/plastic restraints, energy dissipation, rebound energy (whiplash). Vehicle restraint systems and safety features. Hybrid and electric vehicle safety considerations.

Legislation: Introduction to regulations, European directories, USA federal motor vehicle safety standards. Understanding the influence of relevant legislation on vehicle systems design.

Driveline components: Driveline components: Friction clutches, Final drives, Differentials including e-Diff

Manual & automatic transmissions: Description of gearbox layout and gear change mechanisms.

Hybrid and electric vehicles: Basic definitions, HEV and EV architectures, advantages and disadvantages. Electrical and mechanical energy storage technologies including battery management considerations.

Brakes and braking systems: Disc and drum brakes, braking systems – design, dimensioning and evaluation. Materials, manufacturing methods and testing.

Vehicle refinement: Basic details of noise vibration and harshness and attributes for Driveline refinement.

On successful completion of this module you should be able to:

1. Interpret and apply legislative requirements in generating vehicle concepts and designs.

2. Predict resistances to motion, determine powertrain system characteristics, calculate vehicle performance (max. speed, acceleration, gradient, fuel economy etc).

3. Revise vehicle concepts for propulsion driveline systems and components; optimise vehicle performance characteristics for the selected criteria / benchmarks.

4. Assess and critically evaluate vehicle systems and interdependency including vehicle design and ride quality

• To equip you with the skills needed to understand, design and assess single-variable feedback control algorithms using classical control techniques for use in automotive systems.
• To introduce you to MATLAB and Simulink, industry-standard CAD tools for control system design.

The module will provide knowledge in advanced control design tools and techniques and advance analytical methods in designing multivariable controllers with applications in the automotive engineering area. The theory of the multivariable controls will be introduced and then their use will be illustrated and developed by example applications. The theory and applications will be interleaved with selected associated topics (listed below) as appropriate through the module.

The material will be addressed theoretically and practically: all lecture-based teaching will be supported by practical exercises using MATLAB and Simulink.

Prior to the start of the module, students will be expected to ensure that they are familiar with the following key concepts:

o Representation of mechanical and electrical systems using differential equations.

o Representation of linear systems and signals in the time domain, including convolution.

o Use of Laplace transform methods for solving ordinary differential equations.

o Transfer functions, poles and transmission zeros, and frequency responses.

The core syllabus is as follows:
• Creating computer models in MATLAB and Simulink
o Introduction to MATLAB programming
o Introduction to modelling and simulation in Simulink
o Linear system analysis in MATLAB
o Finding operating points and linear models using MATLAB and Simulink

• Classical control concepts
o Key feedback concepts: stability, tracking performance, noise/disturbance rejection
o Relationships between closed-loop functions S(s), T(s) and loop-gain L(s)
o Nyquist stability criterion for stable systems, gain/phase margin and Bode diagram

• Classical control design
o Frequency-domain loop-shaping
o PID design and its relationship to frequency-domain loop-shaping
o Introduction to prefilter design and ‘feed-forward’
o Actuator saturation, noise and integrator wind-up

• Estimator (state observer) design
o Introduction to linear state-space representations
o Estimator design using pole-placement methods

On successful completion of this module you should be able to:
1. Evaluate an automotive system (in terms of its performance, robustness, and sensitivity to noise and disturbances) using classical control concepts and methods.
2. Design feedback control algorithms to meet specified performance requirements using frequency-domain ‘loop-shaping’ methods and PID techniques, and to understand trade-offs and limitations on what can be achieved.
3. Create Simulink simulations of multi-domain automotive systems suitable for performance analysis and control system design, and assess control systems with these models.
4. Evaluate operating points and construct linearized state-space and transfer function modules using MATLAB and Simulink.
5. Construct a linear observer (state estimator) using pole-placement methods, and inspect its behaviour using MATLAB and Simulink.

The aim of this module is to empower students with the capability to analyse, synthesise and evaluate various technologies and integration challenges associated with Electric and Hybrid-Electric Vehicles. The module is structured to provide in-depth knowledge and expertise in the design and development of the main systems, components, and architectures of Electric and Hybrid-Electric Vehicles. The module includes case studies of commercially available Electric and Hybrid-Electric Vehicles, as well as a range of practical workshops.

• • Introduction to Electric and Hybrid-Electric Vehicles systems and powertrain architectures.
  • Energy Storage Systems:
  • Battery technologies: battery chemistries and structures, test procedures, battery modelling and management systems, charging infrastructure
  • Hydrogen in Hybrid-Electric Vehicles: basic principles of operation, FC classification, modelling with irreversibilities
  • Flywheels and ultracapacitors
  • Electric Machines and Power Electronics:
  • Basic Electric Machines theory and design, traction Electric Machine types
  • Power switches, buck/boost converters, H-bridge, three-phase
  • Internal Combustion Engines in Hybrid-Electric Vehicles
  • Energy Management Systems for CO2 reduction, fuel saving, vehicle performance and driveability: basic principles of operation, Rule-Based and Optimal strategies
  • High voltage electrical architectures and the integration of power electronics systems
  • The role of energy recovery systems including regenerative brake strategies
  • Modelling, simulation and analysis of Electric and Hybrid-Electric Vehicles and its sub-systems, using model based approaches
  • Main component sizing against the specified performance objectives
  • Recent Electric and Hybrid-Electric Vehicles technologies case studies
  • A range of practical workshops on Electric and Hybrid-Electric Vehicles, including motor control
  
  
  

On successful completion of this module you should be able to:
1. Evaluate the different Hybrid & Electric powertrain architecture options and be able to propose appropriate solutions within realistic performance, fuel economy, emission and commercial constraints.
2. Evaluate energy storage and energy management technology options for a hybrid or electric vehicle and be able to judge between different technologies relative to a given vehicle application and overall system design.
3. Demonstrate an ability to design and/or size different Hybrid and Electric Vehicle sub-systems, within the context of vehicle usage, weight, packaging, and range constraints.

• To provide a fundamental understanding of vehicle dynamics as applied to wheeled vehicles.


• To introduce you to road vehicle ride and handling, from requirements to analytical modelling and practical viewpoints.

• To link understanding of vehicle dynamics, ride and handling to the practical implications for suspension and steering system design.

The module will provide knowledge in vehicle dynamics ride and handling from subjective and objective requirements to analytical methods in developing passive ride and handling models. 

Core topics:

1. Vehicle Ride, Ride modelling and Terrain modelling
2. Vehicle Handling, steady-state and transient handling
3. Tyre characteristics and tyre modelling
4. Suspension and steering system types, typical designs and practical implications
5. Suspension Kinematics, instantaneous centres of rotation

On successful completion of this module you will be able to:

1. Compose vehicle dynamics models, from first principles, appraising the associated assumptions and implications to numerical simulations.

2. Evaluate vehicle ride and handling performance and the role of tyre and suspension characteristics.

3. Critically evaluate suspension and steering designs, including layout, geometry and materials and their influence on ride and handling.

• Dr Stefano Longo

• To provide a fundamental understanding of physical modelling applied to vehicles mechatronic systems,
• To introduce you to modelling techniques, from basic methodology to graphical modelling and practical viewpoints,
• To illustrate the role of first principle and data-driven modelling.

• Introduction to mathematical modelling,
• Modelling from first principle,
• Newtonian and Lagrangian modelling,
• Electric circuits and networks,
• Modelling from data and system identification,
• Modelling of delays,
• Block diagram reduction,
• Powertrain backward and forward modelling,
• Modelling for vehicle dynamics and tyre-surface interaction,
• Modelling with Matlab/Simulink.

On successful completion of this module you should be able to:

• Compare and criticise the different analogies that can be made between all system dynamics,
• Experiment with fundamental concepts of mechatronics systems to design simplified system dynamics models,
• Evaluate and construct mechatronics models using state-space models derived from system identification, Newtonian equation and Lagrangian equations,
• Construct state-space equations for the purpose of control system design,
• Appraise mechatronics models and the simulations results obtained within the context of practical automotive design concepts, performance and constraints.

• Professor Daniel J. Auger

• To provide knowledge of advanced control engineering theory and techniques and their application to automotive control,
• To introduce you to the tools and methodology associated with multivariable control design techniques,
• To provide you with practical experience in designing and simulating advanced modern controllers within the context of multi-domain automotive systems.

The module will provide knowledge in advanced control design tools and techniques and advance analytical methods in designing multivariable controllers with applications in the automotive engineering area. The theory of the multivariable controls will be introduced and then their use will be illustrated and developed by example applications. The theory and applications will be interleaved with selected associated topics (listed below) as appropriate through the module.

The material will be addressed theoretically and practically: all lecture-based teaching will be supported by practical exercises using MATLAB and Simulink.

Prior to the start of the module, you are expected to have reached a high standard of expertise in advanced classical control and the use of MATLAB and Simulink for control system design. As a guideline, you should have met the intended learning outcomes for the module ‘Automotive Control and Simulation’ before commencing this course. Students who have not taken this module should ensure they do sufficient pre-work prior to the module.




Modelling multivariable systems:

• Describing multivariable systems using state-space representations,
• Using norms to describe the sizes and behaviours of signals and systems,
• Modelling uncertainty, noise and nonlinearities,
• The Nyquist stability criterion and robustness.

 

Using time-based optimisation in multivariable control:

• Representing feedback using state-space techniques,
• Pole-placement techniques,
• Optimal control using the Linear-Quadratic Regulator (LQR),
• Introduction to Model-Predictive Control (MPC).

 

State estimator design:

• Multivariable estimator design using pole-placement techniques
• Optimal estimator design for linear systems using the Kalman Filter
• Introduction to optimal control using Linear-Quadratic-Gaussian (LQG) techniques
• Introduction to nonlinear Kalman filtering techniques

 

Using norm-based optimisation to design robust controllers:

• H-infinity control methods: ‘mixed sensitivity’ and ‘H-infinity loop-shaping’
• Estimating robust performance using the nu-gap metric

 

Reference conditioning using prefilters and two degree-of-freedom compensators (covered in outline only).

Students will be provided with electronic copies of lecture slides, the lecturer’s handwritten notes and computer programs.  Students are expected to complement this with their own notes.

Recordings of the lectures will not be generally available for this module, though exceptions may be made for students who are unable to attend due to exceptional circumstances that are relevant, unexpected and external.

On successful completion of this module you should be able to:

• Create theoretical and computer models of multivariable automotive systems suitable for use in control design,
• Apply different advanced control techniques to automotive control problems,
• Design control algorithms for automotive systems using MATLAB and Simulink (commercial software packages),
• Design state estimators for multivariable automotive control systems using established techniques,
• Judge the suitability of a given control technique to a particular application in the context of automotive control.

• Dr Stefano Longo

Within the context of modern automotive control system, the aim of this module is for you to critically evaluate the different technologies and methods required for the efficient vehicle implementation, validation and verification of the automotive mechatronic system.

Course content includes:

• A review of modern automotive control hardware requirements and architectures,
• The evaluation of current and future vehicle networking technologies including, CAN, LIN, MOST and Flex-ray,
• The evaluation of control rapid prototyping techniques to design and calibrate the control algorithm,
• The use of modern validation and verification methods, such as software-in-the-loop, and hardware-in-the-loop techniques,
• The role of Functional Safety and ISO26262 within the overall control system life-cycle,
• The evaluation of the interdependency between software engineering and control system design within the automotive industry including the use of software auto-coding techniques for production and the use of advanced test methods for the validation of safety-critical systems.

 

On successful completion of this module you should be able to:

• Analyse the components of an automotive control systems and its implementation,
• Design and implement a digital controller,
• Evaluate the effect of sampling times, communication delays and quantization errors in a feedback loop,
• Construct efficient Matlab code for data coding/decoding and control algorithm implementation,
• Appraise the purpose of the ISO26262 functional safety standard and the AUTOSAR standardized automotive software design.

The aim of this module is to cover a range of applications of Control Theory and Artificial Intelligence techniques in different components of a modern vehicle including engines, electric motors, energy storage, steering, chassis, suspensions, advanced driver-assistance systems, etc.

• Motor control
• Engine control
• Battery state estimation and control
• Electric and hybrid-electric powertrain control systems
• Vehicle steering control
• Vehicle suspensions and chassis control
• ADAS and autonomous driving

On successful completion of this module you should be able to:

1. Critically evaluate the physical configuration of a vehicle sub-system and be able to formulate new control design solutions appropriate for integration within a vehicle.
2. Appraise a set of vehicle performance targets for higher levels of automation and safety, more energy conservation and less environmental impacts and be able to select the most appropriate control methods and design techniques to meet the vehicle specification.
3. Analyse and evaluate different simulation models including vehicle control architectures.