Research and Implement of PMSM Regenerative Braking Control for Electric Vehicle

As the society pays more and more attention to the environment pollution and energy crisis, the electric vehicle (EV) development also entered in a new era. With the development of motor speed control technology and the improvement of motor performance, although the dynamic performance and economical cost of EVs are both better than the internal-combustion engine vehicle (ICEV), the driving range limit and charging station distribution are two major problems which limit the popularization of EVs. In order to extend driving range for EVs, regenerative braking (RB) emerges which is able to recover energy during the braking process to improve the energy efficiency. This thesis aims to investigate the RB based pure electric braking system and its implementation. There are many forms of RB system such as fully electrified braking system and blended braking system (BBS) which is equipped both electric RB system and hydraulic braking (HB) system. In this thesis the main research objective is the RB based fully electrified braking system, however, RB system cannot satisfy all braking situation only by itself. Because the regenerating electromagnetic torque may be too small to meet the braking intention of the driver when the vehicle speed is very low and the regenerating electromagnetic torque may be not enough to stop the vehicle as soon as possible in the case of emergency braking. So, in order to ensure braking safety and braking performance, braking torque should be provided with different forms regarding different braking situation and different braking intention. In this thesis, braking torque is classified into three types. First one is normal reverse current braking when the vehicle speed is too low to have enough RB torque. Second one is RB torque which could recover kinetic energy by regenerating electricity and collecting electric energy into battery packs. The last braking situation is emergency where the braking torque is provided by motor plugging braking based on the optimal slip ratio braking control strategy. Considering two indicators of the RB system which are regenerative efficiency and braking safety, a trade-off point should be found and the corresponding control strategy should be designed. In this thesis, the maximum regenerative efficiency is obtained by a braking torque distribution strategy between front wheel and rear wheel based on a maximum available RB torque estimation method and ECE-R13 regulation. And the emergency braking performance is ensured by a novel fractional-order integral sliding mode control (FOISMC) and numerical simulations show that the control performance is better than the conventional sliding mode controller

Energy recovery strategy for regenerative braking system of intelligent four-wheel independent drive electric vehicles

Regenerative braking system can recovery energy in various electric vehicles. Considering large computation load of global optimization methods, most researches adopt instantaneous or local algorithms to optimize the recuperation energy, and incline to study straight deceleration processes. However, uncertain drivers' intentions limit the potential exploration of economy improvement, and simple test conditions do not reflect the complexity of actual driving cycles. Herein, an innovative control architecture is designed for intelligent vehicles to overcome these challenges to some extent. Compared with traditional vehicles, driverless ones would eliminate drivers' interferences, and have more freedoms to optimize energy recovery, route tracking and dynamics stability. Specifically, a series regenerative braking system is designed, and then a three‐level control architecture is first proposed to coordinate three performances. In the top layer, some rules with maximum recuperation energy is exploited off‐line for optimising the velocity and control commands on‐line. In the middle layer, local algorithm is used to track the commands and complex routes for optimal energy from a global perspective. In the bottom layer, hydraulic and regenerative toques are allocated. Tests are conducted to demonstrate the effectiveness of the design and control schemes

Integration of anti-lock braking system and regenerative braking for hybrid/electric vehicles

Vehicle electrification aims at improving energy efficiency and reducing pollutant emissions which creates an opportunity to use the electric machines (EM) as Regenerative Braking System (RBS) to support the friction brake system. Anti-lock Braking System (ABS) is part of the active safety systems that help drivers to stop safely during panic braking while ensuring the vehicle’s stability and steerability. Nevertheless, the RBS is deactivated at a safe (low) deceleration threshold in favour of ABS. This safety margin results in significantly less energy recuperation than what would be possible if both RBS and ABS were able to operate simultaneously. Vehicle energy efficiency can be improved by integrating RBS and friction brakes to enable more frequent energy recuperation activations, especially during high deceleration demands. The main aim of this doctoral research is to design and implement new wheel slip control with torque blending strategies for various vehicle topologies using four, two and one EM. The integration between the two braking actuators will improve the braking performance and energy efficiency of the vehicle. It also enables ABS by pure EM in certain situations where the regenerative brake torque is sufficient. A novelmethod for integrating the wheel slip control and torque blending is developed using Nonlinear Model Predictive Control (NMPC). The method is well known for the optimal performance and enforcement of critical control and state constraints. A linear MPC strategy is also developed for comparison purpose. A pragmatic brake torque blending algorithm using Daisy-Chain with sliding mode slip control is also developed based on a pre-defined energy recuperation priority. Simulation using high fidelity model using co-simulation in Matlab/Simulink and CarMaker is used to validate the developed strategies. Different test patterns are used to evaluate the controllers’ performance which includes longitudinal and lateral motions of the vehicle. Comparison analysis is done for the proposed strategies for each case. The capability for real-time implementation of the MPC controllers is assessed in simulation testing using dSPACE hardware

A Comprehensive Review on Hybrid and Electric Vehicle Energy Control and Management Strategies

We show a new technology to manage solid waste services through optimization methods (on sectoring, routing costs, and resources). This technology is called optimized planning and integrated logistics management (OPILM). It is being applied to Brazilian municipalities as it attends to their major natural features. The technology is formed by a framework of computational systems that uses optimization methods from sector arc routing and scheduling, fleet and staff scheduling, using also mobile smartphone apps. We present some of the results of real cases evaluated for residential refuse collection and selective waste collection in two Brazilian cities (Petrópolis/RJ and Bom Jesus dos Perdões/SP). The plan implementations achieved 17.9% from actual fixed and variable cost savings for sectors (vehicles and workers) and routes (time and distances) for residential refuse collection in Petrópolis/RJ. For the selective waste collection, we detail how we made our project to Bom Jesus dos Perdões/SP. We also present the returns considering costs involved in the management of the operational level and amortized by the investment required to use and apply the proposed technology for Petrópolis/SP

A series elastic brake pedal for improving driving performance under regenerative braking

Electric and hybrid vehicles are favored to decrease the carbon footprint on the planet. The electric motor in these vehicles serves a dual purpose. The use of electric motor for deceleration, by converting the kinetic energy of the vehicle into electrical energy to be stored in the battery is called regenerative braking. Regenerative braking is commonly employed by electrical vehicles to signi cantly improve energy e ciency and to help to meet emission standards. When the regenerative and friction brakes are simultaneously activated by the driver interacting with the brake pedal, the conventional haptic brake pedal feel is disturbed due to the regenerative braking. In particular, while there exists a physical coupling between the brake pedal and the conventional friction brakes, no such physical coupling exists for the regenerative braking. As a result, no reaction forces are fed back to the brake pedal, resulting in a unilateral power ow between the driver and the vehicle. Consequently, the relationship between the brake pedal force and the vehicle deceleration is strongly in uenced by the regenerative braking. This results in a unfamiliar response of the brake pedal, negatively impacting the driver's performance and posing a safety concern. The reaction forces due to regenerative braking can be fed back to the brake pedal, through actuated pedals that re-establish the bilateral power ow to recover the natural haptic pedal feel. We propose a force-feedback brake pedal with series elastic actuation to preserve the conventional brake pedal feel during regenerative braking. The novelty of the proposed design is due to the deliberate introduction of a compliant element between the actuator and the brake pedal whose de ections are measured to estimate interaction forces and to perform closed-loop force control. Thanks to its series elasticity, the force-feedback brake pedal can utilize robust controllers to achieve high delity force control, possesses favorable output impedance characteristics over the entire frequency spectrum, and can be implemented in a compact package using low-cost components. We introduce pedal feel compensation algorithms to recover the missing regenerative brake forces on the brake pedal. The proposed algorithms are implemented for both two-pedal cooperative braking and one-pedal driving conditions. For those driving conditions, the missing pedal feedback due to the regenerative brake forces are rendered through the active pedal to recover the conventional pedal force mapping. In two-pedal cooperative braking, the regenerative braking is activated by pressing the brake pedal, while in one-pedal driving the activation takes place as soon as the throttle pedal is released. The applicability and e ectiveness of the proposed series elastic brake pedal and haptic pedal feel compensation algorithms in terms of driving safety and performance have been investigated through human subject experiments. The experiments have been conducted using a haptic pedal feel platform that consists of a SEA brake pedal, a torque-controlled dynamometer, and a throttle pedal. The dynamometer renders the pedal forces due to friction braking, while the SEA brake pedal renders the missing pedal forces due to the regenerative braking. The throttle pedal is utilized for the activation of regenerative braking in one-pedal driving. The simulator implements a vehicle pursuit task similar to the CAMP protocol and provides visual feedback to the participant. The e ectiveness of the preservation of the natural brake pedal feel has been studied under two-pedal cooperative braking and one-pedal driving scenarios. The experimental results indicate that pedal feel compensation can signi cantly decrease the number of hard braking instances, improving safety for both two-pedal cooperative braking and one-pedal driving. Volunteers also strongly prefer compensation, while they equally prefer and can e ectively utilize both two-pedal and one-pedal driving conditions. The bene cial e ects of haptic pedal feel compensation on safety is evaluated to be larger for the two-pedal cooperative braking condition, as lack of compensation results in sti ening/softening pedal feel characteristics in this cas

Control of a hybrid electric vehicle with predictive journey estimation

Battery energy management plays a crucial role in fuel economy improvement of charge-sustaining parallel hybrid electric vehicles. Currently available control strategies consider battery state of charge (SOC) and driver’s request through the pedal input in decision-making. This method does not achieve an optimal performance for saving fuel or maintaining appropriate SOC level, especially during the operation in extreme driving conditions or hilly terrain. The objective of this thesis is to develop a control algorithm using forthcoming traffic condition and road elevation, which could be fed from navigation systems. This would enable the controller to predict potential of regenerative charging to capture cost-free energy and intentionally depleting battery energy to assist an engine at high power demand. The starting point for this research is the modelling of a small sport-utility vehicle by the analysis of the vehicles currently available in the market. The result of the analysis is used in order to establish a generic mild hybrid powertrain model, which is subsequently examined to compare the performance of controllers. A baseline is established with a conventional powertrain equipped with a spark ignition direct injection engine and a continuously variable transmission. Hybridisation of this vehicle with an integrated starter alternator and a traditional rule-based control strategy is presented. Parameter optimisation in four standard driving cycles is explained, followed by a detailed energy flow analysis. An additional potential improvement is presented by dynamic programming (DP), which shows a benefit of a predictive control. Based on these results, a predictive control algorithm using fuzzy logic is introduced. The main tools of the controller design are the DP, adaptive-network-based fuzzy inference system with subtractive clustering and design of experiment. Using a quasi-static backward simulation model, the performance of the controller is compared with the result from the instantaneous control and the DP. The focus is fuel saving and SOC control at the end of journeys, especially in aggressive driving conditions and a hilly road. The controller shows a good potential to improve fuel economy and tight SOC control in long journey and hilly terrain. Fuel economy improvement and SOC correction are close to the optimal solution by the DP, especially in long trips on steep road where there is a large gap between the baseline controller and the DP. However, there is little benefit in short trips and flat road. It is caused by the low improvement margin of the mild hybrid powertrain and the limited future journey information. To provide a further step to implementation, a software-in-the-loop simulation model is developed. A fully dynamic model of the powertrain and the control algorithm are implemented in AMESim-Simulink co-simulation environment. This shows small deterioration of the control performance by driver’s pedal action, powertrain dynamics and limited computational precision on the controller performance

Switching nonlinear model predictive control of collaborative railway vehicles in catenary grids

This article contributes to the railway control field by proposing a novel approach capable of making trains collaborate, while also minimizing both traction energy and power line losses in catenary grids. The train dynamics are captured by a combination of four operating modes, so that the formulation of a switched control problem naturally applies. This model is interfaced with that of the catenary grid, consisting of the electrical substations and transmission lines over the track. Relying on these models, an eco-drive control system is proposed based on an original switching nonlinear model predictive control (SNMPC). Being collaborative-conceived, the new SNMPC is compared and evaluated against a noncollaborative version of the controller by means of simulation case studies relying on real-world test data, a validated train model, and measured track topology. We obtain that the proposed SNMPC outperforms the noncollaborative counterpart both in terms of traction energy and energy losses on the train rheostats and over the electrical lines. Thus, we demonstrate that the proposed SNMPC for collaborative eco-drive, based on the energy exchange between trains, has a potential positive impact on railway systems in catenary grids

Control of AC/DC microgrids with renewables in the context of smart grids including ancillary services and electric mobility

Microgrids are a very good solution for current problems raised by the constant growth of load demand and high penetration of renewable energy sources, that results in grid modernization through “Smart-Grids” concept. The impact of distributed energy sources based on power electronics is an important concern for power systems, where natural frequency regulation for the system is hindered because of inertia reduction. In this context, Direct Current (DC) grids are considered a relevant solution, since the DC nature of power electronic devices bring technological and economical advantages compared to Alternative Current (AC). The thesis proposes the design and control of a hybrid AC/DC Microgrid to integrate different renewable sources, including solar power and braking energy recovery from trains, to energy storage systems as batteries and supercapacitors and to loads like electric vehicles or another grids (either AC or DC), for reliable operation and stability. The stabilization of the Microgrid buses’ voltages and the provision of ancillary services is assured by the proposed control strategy, where a rigorous stability study is made. A low-level distributed nonlinear controller, based on “System-of-Systems” approach is developed for proper operation of the whole Microgrid. A supercapacitor is applied to deal with transients, balancing the DC bus of the Microgrid and absorbing the energy injected by intermittent and possibly strong energy sources as energy recovery from the braking of trains and subways, while the battery realizes the power flow in long term. Dynamical feedback control based on singular perturbation analysis is developed for supercapacitor and train. A Lyapunov function is built considering the interconnected devices of the Microgrid to ensure the stability of the whole system. Simulations highlight the performance of the proposed control with parametric robustness tests and a comparison with traditional linear controller. The Virtual Synchronous Machine (VSM) approach is implemented in the Microgrid for power sharing and frequency stability improvement. An adaptive virtual inertia is proposed, then the inertia constant becomes a system’s state variable that can be designed to improve frequency stability and inertial support, where stability analysis is carried out. Therefore, the VSM is the link between DC and AC side of the Microgrid, regarding the available power in DC grid, applied for ancillary services in the AC Microgrid. Simulation results show the effectiveness of the proposed adaptive inertia, where a comparison with droop and standard control techniques is conducted.As Microrredes são uma ótima solução para os problemas atuais gerados pelo constante crescimento da demanda de carga e alta penetração de fontes de energia renováveis, que resulta na modernização da rede através do conceito “Smart-Grids”. O impacto das fontes de energia distribuídas baseados em eletrônica de potência é uma preocupação importante para o sistemas de potência, onde a regulação natural da frequência do sistema é prejudicada devido à redução da inércia. Nesse contexto, as redes de corrente contínua (CC) são consideradas um progresso, já que a natureza CC dos dispositivos eletrônicos traz vantagens tecnológicas e econômicas em comparação com a corrente alternada (CA). A tese propõe o controle de uma Microrrede híbrida CA/CC para integrar diferentes fontes renováveis, incluindo geração solar e frenagem regenerativa de trens, sistemas de armazenamento de energia como baterias e supercapacitores e cargas como veículos elétricos ou outras (CA ou CC) para confiabilidade da operação e estabilidade. A regulação das tensões dos barramentos da Microrrede e a prestação de serviços anciliares são garantidas pela estratégia de controle proposta, onde é realizado um rigoroso estudo de estabilidade. Um controlador não linear distribuído de baixo nível, baseado na abordagem “System-of-Systems”, é desenvolvido para a operação adequada de toda a rede elétrica. Um supercapacitor é aplicado para lidar com os transitórios, equilibrando o barramento CC da Microrrede, absorvendo a energia injetada por fontes de energia intermitentes e possivelmente fortes como recuperação de energia da frenagem de trens e metrôs, enquanto a bateria realiza o fluxo de potência a longo prazo. O controle por dynamical feedback baseado numa análise de singular perturbation é desenvolvido para o supercapacitor e o trem. Funções de Lyapunov são construídas considerando os dispositivos interconectados da Microrrede para garantir a estabilidade de todo o sistema. As simulações destacam o desempenho do controle proposto com testes de robustez paramétricos e uma comparação com o controlador linear tradicional. O esquema de máquina síncrona virtual (VSM) é implementado na Microrrede para compartilhamento de potência e melhoria da estabilidade de frequência. Então é proposto o uso de inércia virtual adaptativa, no qual a constante de inércia se torna variável de estado do sistema, projetada para melhorar a estabilidade da frequência e prover suporte inercial. Portanto, o VSM realiza a conexão entre lado CC e CA da Microrrede, onde a energia disponível na rede CC é usada para prestar serviços anciliares no lado CA da Microrrede. Os resultados da simulação mostram a eficácia da inércia adaptativa proposta, sendo realizada uma comparação entre o controle droop e outras técnicas de controle convencionais

Optimal control of a flywheel-based automotive kinetic energy recovery system

This thesis addresses the control issues surrounding flywheel-based Kinetic Energy Recovery Systems (KERS) for use in automotive vehicle applications. Particular emphasis is placed on optimal control of a KERS using a Continuously Variable Transmission (CVT) for volume car production, and a wholly simulation-based approach is adopted. Following consideration of the general control issues surrounding KERS operation, a simplified system model is adopted, and the scope for use of optimal control theory is explored. Both Pontryagin’s Maximum Principle, and Dynamic Programming methods are examined, and the need for numerical implementation established. With Dynamic Programming seen as the most likely route to practical implementation for realistic nonlinear models, the thesis explores several new strategies for numerical implementation of Dynamic Programming, capable of being applied to KERS control of varying degrees of complexity. The best form of numerical implementation identified (in terms of accuracy and efficiency) is then used to establish via simulation, the benefits of optimal KERS control in comparison with a more conventional non-optimal strategy, showing clear benefits of using optimal control

Mild Hybrid Electric Vehicles: Powertrain Optimization for Energy Consumption, Driveability and Vehicle Dynamics Enhancements

This thesis deals with the modeling, the design and the control of mild hybrid electric vehicles. The main goal is to develop accurate design tools and methodologies for preliminary system and component level analysis. Particular attention is devoted to the configuration in which an electric machine is mounted on the rear axle of a passenger car. The use of such a machine in parallel with the internal combustion engine allows one to exploit different functionalities that are able to reduce the overall fuel consumption of the vehicle. In addition, the indirect coupling between the thermal and the electric machine, realized through the road and not by means of mechanical couplers, together with the position of the latter in the overall vehicle chassis system, enables such an architecture to be efficient both from the energy recovery and the full electric driving point of view. Chapter 1 introduces the problem of fuel consumption and emissions reduction in the overall world context and presents the main hybrid architectures available. Chapter 2 is devoted to the study of the influence of the electric machine position in the powertrain regarding the regenerative braking potentialities concerned. The model considered for the analysis will be described on each of its subcomponents. The braking performance of the vehicle in electric mode is presented considering no losses in the electric powertrain (electric motor, battery, inverter). Chapter 3 is dedicated to the design of an electric machine for a rear axle powertrain. The specifications of such machine are optimized considering both the vehicle and the application under analysis. The design takes into account analytical techniques for the computation of electrical parameters (such as phase and DC currents) and the torque - speed map, as well as numerical ones for its thermal behavior. In Chapter 4 the electrical and thermal characteristics of the designed electric motor are implemented in the model presented in Chapter 2. The overall vehicle model is therefore used both to assess a simple torque split strategy between thermal and electric machine and to perform an optimal sizing of the battery considering all the limitations imposed by the electric powertrain (e. g. maximum currents, maximum temperatures). Chapter 5 makes a step forward and analyzes the different implications that the use of the rear axle electric motor to brake the vehicle has on the vehicle dynamics. Open loop analysis will present a degradation of the vehicle handling comfort caused by the introduction of an oversteering moment to the vehicle. Through the use of a simplified vehicle model, the introduced oversteering yaw moment is evaluated, while a control strategy based on a new stability detector will show how to find a trade off between handling comfort and regenerable energy. At last, Chapter 6 deals with the problem of longitudinal driving comfort. Drivelines and chassis are lightly damped systems and the application of an impulsive torque imposed by the driver can cause the vehicle longitudinal acceleration (directly perceived by the driver) to be oscillating and non smooth. A sensitivity analysis on a conventional powertrain is presented demonstrating which of the different components are more influential in the different modes of vibration, and possible solutions to improve the driveability are proposed. One of these relates to the use of the rear axle electric machine in order to give more responsiveness to the vehicle. Finally, concluding remarks are given in Chapter 7