Integrated braking control for electric vehicles with in-wheel propulsion and fully decoupled brake-by-wire system

This paper introduces a case study on the potential of new mechatronic chassis systems for battery electric vehicles, in this case a brake-by-wire (BBW) system and in-wheel propulsion on the rear axle combined with an integrated chassis control providing common safety features like anti-lock braking system (ABS), and enhanced functionalities, like torque blending. The presented controller was intended to also show the potential of continuous control strategies with regard to active safety, vehicle stability and driving comfort. Therefore, an integral sliding mode (ISM) and proportional integral (PI) control were used for wheel slip control (WSC) and benchmarked against each other and against classical used rule-based approach. The controller was realized in MatLab/Simulink and tested under real-time conditions in IPG CarMaker simulation environment for experimentally validated models of the target vehicle and its systems. The controller also contains robust observers for estimation of non-measurable vehicle states and parameters e.g., vehicle mass or road grade, which can have a significant influence on control performance and vehicle safety

Model-free intelligent Control for anti-lock braking systems on rough terrain

Advances made in Advanced Driver Assistance Systems such as Antilock Braking Systems (ABS), have significantly improved the safety of road vehicles. ABS enhances the braking performance and steerability of a vehicle under severe braking conditions. However, ABS performance degrades on rough terrain. This is largely due to noisy measurements, the type of ABS control algorithm used, and the excitation of complex dynamics such as higher order tyre mode shapes that are neglected in the control strategy. This study proposes a model-free intelligent control technique with no modelling constraints that can overcome these un-modelled dynamics and parametric uncertainties. The Double Deep Q-learning Network algorithm with the Temporal Convolutional Network is presented as the intelligent control algorithm. The model is initially trained with a simplified single wheel model. The initial training data is transferred to and then enhanced by using a validated full-vehicle model including a physics-based tyre model, a 3D rough road profile with added stochasticity. The performance of the newly developed ABS controller is compared to a Bosch algorithm tuned for off-road use. Simulation results show a generalizable and robust control algorithm that can prevent wheel lockup over rough terrain without significantly deteriorating the vehicle’s stopping distance on smooth roadsDissertation (MEng (Mechanical Engineering))--University of Pretoria, 2022.Mechanical and Aeronautical EngineeringMEng (Mechanical Engineering)Unrestricte

ABS braking on rough terrain

This aim of this project may be condensed to the following question: Is there an improvement achievable in the braking performance of a vehicle on a rough road? Several follow-up questions arise from the above problem statement: a) What are the causes of the unsatisfactory stopping time and distance when braking on a rough road and how can they be addressed? b) Can the off-road braking of a vehicle be modelled mathematically? c) What are the criteria used to evaluate the on-road braking performance of a vehicle and can the off-road braking performance of a vehicle be evaluated using the same criteria? d) Can the off-road braking performance be improved without compromising the on-road performance? An extensive literature survey is done on existing research addressing these four questions. It is found that, although the literature acknowledges that the braking performance of a vehicle deteriorates under off-road conditions, very little has been done to address it. Two main factors influencing the braking performance are identified, namely the ABS algorithm inputs and tyre force generation characteristics. An experimentally validated vehicle model is developed that serves as the basis from which the research question will be addressed. An FTire model is parameterised and used as the tyre model throughout this study. Three measured off-road terrain profiles are used. The first step in addressing the research question is developing a performance evaluation technique that can easily, quantifiably and visually compare the braking performance of several ABS systems on any road surface, in any condition. The performance evaluation technique considers the stopping distance, longitudinal deceleration, lateral path offset error, and yaw rate error as metrics. The second step is investigating one of the common assumptions found in ABS algorithms, namely that the roll radius is constant. This is investigated experimentally and it is concluded that the assumption is valid on smooth and rough road surfaces when using the kinematic definition of the roll radius, but invalid when using the kinetic definition of the roll radius. Investigation of the influence of the tyre force generation characteristics on the braking performance is the third step. It is found that the tyre normal force variation and corresponding suspension force variation correlates closely with the braking performance. A higher suspension force variation is associated with longer stopping distances. The final step is the development of a three step control strategy that aims to reduce the suspension force variation. This is done by estimating the wheel hop using easy to measure states, predicting the suspension force variation based on these estimates, and finally selecting the ideal suspension configuration. The control strategy, called the WiSDoM algorithm, was evaluated by doing several simulations on the three off-road road profiles, with different braking points as the only changed variable. The WiSDoM algorithm’s performance was compared with the baseline vehicle performance and found to decrease the stopping distance on all three off-road road profiles, without negatively affecting the stability of the vehicle. The WiSDoM algorithm did not have a significant influence on the braking performance on a smooth road.Thesis (PhD)--University of Pretoria, 2017.DAAD-NRF Joint ScholarshipMechanical and Aeronautical EngineeringPhD (Mechanical Engineering)Unrestricte

Development of a vehicle dynamics controller for obstacle avoidance

As roads become busier and automotive technology improves, there is considerable potential for driver assistance systems to improve the safety of road users. Longitudinal collision warning and collision avoidance systems are starting to appear on production cars to assist drivers when required to stop in an emergency. Many luxury cars are also equipped with stability augmentation systems that prevent the car from spinning out of control during aggressive lateral manoeuvres. Combining these concepts, there is a natural progression to systems that could assist in aiding or performing lateral collision avoidance manoeuvres. A successful automatic lateral collision avoidance system would require convergent development of many fields of technology, from sensors and instrumentation to aid environmental awareness through to improvements in driver vehicle interfaces so that a degree of control can be smoothly and safely transferred between the driver and vehicle computer. A fundamental requirement of any collision avoidance system is determination of a feasible path that avoids obstacles and a means of causing the vehicle to follow that trajectory. This research focuses on feasible trajectory generation and development of an automatic obstacle avoidance controller that integrates steering and braking action. A controller is developed to cause a specially modified car (a Mercedes `S' class with steer-by-wire and brake-by-wire capability) to perform an ISO 3888-2 emergency obstacle avoidance manoeuvre. A nonlinear two-track vehicle model is developed and used to derive optimal controller parameters using a series of simulations. Feedforward and feedback control is used to track a feasible reference trajectory. The feedforward control loops use inverse models of the vehicle dynamics. The feedback control loops are implemented as linear proportional controllers with a force allocation matrix used to apportion braking effort between redundant actuators. Two trajectory generation routines are developed: a geometric method, for steering a vehicle at its physical limits; and an optimal method, which integrates steering and braking action to make full use of available traction. The optimal trajectory is obtained using a multi-stage convex optimisation procedure. The overall controller performance is validated by simulation using a complex proprietary model of the vehicle that is reported to have been validated and calibrated against experimental data over several years of use in an industrial environment

Investigation on electric motor braking control system for electric powered wheelchair

In recent years, research on Electric Powered Wheelchair (EPW) has been widely studied due to its high importance of mobility for disabled people. During descent on a slope, the manual braking system is commonly used to control the speed by gripping the brake lever. However, the task becomes difficult if the user is an elderly or paralyzed due to their body’s deficiencies. As a result, the possibilities of collision and injuries to occur are high. In this study, the automatic electric motor braking control that is known as Hill Descent Control (HDC) is proposed to increase the safety of EPW during descending on slopes. Since the electric motor has an advantage which can generate the torque during braking, the plugging braking is integrated with the HDC system to control the speed of the EPW according to the desired speed from the user. The analysis of this study is divided into three phases; investigation of braking performance using electrical braking, development of active braking control system in the embedded system as well as the simulation environment and analysis on active braking control system in experimental and simulation work. From the experimental results, the plugging brake is most suitable to integrate with the active brake control system compared to the regenerative and dynamic brake. In the plugging brake, by changing the plugging voltage from 0.5 V to 4.5 V, a variety of dynamic behaviour effects such as braking distance, tire speed and slip ratio can be achieved. Meanwhile, from the analysis of active braking control system that was integrated with plugging braking, both of the experimental and simulation analysis results show the speed of EPW can be maintained at the desired speed o

In Depth Analysis of Power Balance, Handling, and the Traction Subsystem of an Articulated Skid-Steering Robot for Sustainable Agricultural Monitoring

This paper reports on the energy balance test performed on Agri.Q, an eight-wheel articulated robot intended to be a sustainable monitoring tool within the precision agriculture paradigm, and proposes an in-depth analysis of the traction subsystem in order to develop an appropriate traction allocation strategy to improve navigation through hilly or mountainous crops. Tests were conducted on the contribution of the orientable photovoltaic panel to the mission duration and overall sustainability, showing that a suitable mission plan, including dedicated charging phases, could significantly increase the robot’s operating time. A series of simulations of circular trajectories of different curvature and at different longitudinal velocities on flat ground were performed, with the aim of mapping the robot’s behaviour at steady state. The results of the simulations were analysed, paying particular attention to the required torques, manoeuvrability and forces exchanged on the ground. The simulations conducted demonstrated and extended previous results obtained on similar robotic architectures, which suffer from significant understeer behaviour due to significant lateral wheel slip during turning. They also showed the limitations of currently employed traction motors, but also the advantages of a proper traction allocation strategy involving the rear module. Article highlights. Agri.Q energy balance tests have been carried out to assess its endurance and sustainability The traction and handling behaviours of Agri.Q were mapped and discussed in detail in order to improve them Agri.Q has proven to be a basis for the future implementation of precision agriculture to advance the SDG