Switching Control for Smooth Mode Changes in Hybrid Electric Vehicles
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1 Switching Control for Smooth Mode Changes in Hybrid Electric Vehicles Kerem Koprubasi (1), Eric Westervelt (2), Giorgio Rizzoni (3) (1) PhD Student, (2) Assistant Professor, (3) Professor Department of Mechanical Engineering Center for Automotive Research The Ohio State University Applicazioni e prospettive del controllo nei veicoli DEI, Politecnico di Milano May 10 th, 2007
2 Motivation 97% of NA transportation is dependent on petroleum 27.9% of oil consumption is for transportation 5.6% Useful Energy 25.6% of our energy from imported oil Negative impact on economy Goal: Sustainable mobility 1
3 Motivation Project Goals 1. Develop a control-oriented model of the Challenge-X vehicle to analyze longitudinal drivability. 2. Utilize analysis and design tools from hybrid systems theory for model-based control of drivability. Focus: Realize smooth mode changes (particularly for electric launch to hybrid). Definition -- Drivability Driver's response to unexpected changes in the longitudinal acceleration of a vehicle. Frequency Range of Interest ~ 1-10 Hz (human body mechanical resonances ~ 4-8 Hz)
4 Common Drivability Issues Conventional Vehicles Pedal tip-in tip-out + Hybrid Electric Vehicles Engine start-stop Torque Hole Gear shifting Control strategy mode changes
5 Challenge-X X Competition 17 North American universities compete in a 4-year advanced vehicle development competition. Crossover SUV Higher fuel economy Reduced pollutant emissions Improved performance, utility, safety, & consumer acceptability Ohio State Challenge-X Hybrid Vehicle
6 Selected Vehicle Architecture Front Wheels Rear Wheels 1.9L Diesel Engine 6-Speed Automatic Transmission 67 kw Traction Electric Machine 10 kw Belted Starter Alternator 300V Nominal Ni-MH Battery Pack Dual LNT Exhaust After-treatment System DC/DC Converter for 12V accessories
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15 PART 1: MODELING AND VALIDATION
16 Modeling Tools: Quasi-Static CX-SIM FUDS FHDS Quasi-Static Vehicle Model Fuel Economy and Basic Performance Evaluation Stock Control Strategy Development and Tuning HEV CX-Sim: Predicted Fuel Economy (mpg gasoline equivalent) CX-Sim: Main Interface CX-Sim: HEV Powertrain
17 CX-DYN Low-to-Mid Frequency Dynamic HEV Model Modeling Tools: Dynamic Prediction of Drivability - Gear Shift Transients - Driveline Shuffle - Torque Holes - Actuator Delays Driveline Model Used as a Basis for CX-Dyn
18 Dynamic Model: Engine & BSA A 1.9L diesel engine and a belted starter alternator (BSA) provide torque for the front drive. The engine air-fuel dynamics are simplified according to the required modeling bandwidth. Most engine parameters are identified based on experimental data. θ = f ω ) τ = f ω, T ) comb ( ICE EQ ICE air J = J + J BSA ( ICE ICE,req
19 Transmission & Torque Converter 6-speed automatic transmission A planetary gearset connected to a 2-stage Ravigneaux gearset. Gear couplings are assumed to be rigid in the model. Quasi-static torque converter dynamics: If ω TC,T / ω TC,P < 0.85 If ω TC,T / ω TC,P > TPUMP = C1ω ICE + C2ωICEωTC, T + C3ω 2 2 TC, T TPUMP = TTURB = C ω ICE + C8ωICEωTC, T + C9ω 2 2 T = C ω + C ω ω + C ω TURB 4 ICE 5 ICE TC, T 6 TC, T 7 TC, T
20 Transmission Schematic Transmission Stick Diagram PGS: Planetary Gear Set RGS: Ravigneaux Gear Set Torque Converter Clutch and Brake Schematic Ref: SAE Paper Clutches: C-1, C-2, C3; F-1 (One-way) Brakes: B-1, B-2
21 Dynamics of Rear Axle Rear axle is driven by a 67 kw AC induction machine. The motor is directly connected to a modified rear differential. Half-shaft and wheel elasticities are lumped into an equivalent torsional compliance. Braking is achieved by a combination of hydraulic and regenerative braking torques.
22 Control Strategy Operating Modes The control strategy has the capability of operating the vehicle in the following modes: Vehicle Idle Engine OFF, only electrical accessories active Electric Only Engine OFF, power delivered through the EM Engine Start-Stop BSA starts or stops engine under suitable conditions Hybrid (ECMS) Power delivered to road via a combination of engine and two electric machines. Deceleration Kinetic energy recuperated via EM recharging battery
23 Preliminary Validation Results Preliminary model validation is performed using data from CX 06 competition. Quasi-Static Validation Vehicle Tech Specs Fuel Economy (mpgge*) Simulation (Combined) 25.8 Simulation (US06) 19.1 Competition Result 25 * mppge: mpg gasoline equivalent (battery charge included) Acceleration Simulation (0-60 mph) Competition (0-60 mph) Simulation (50-70 mph) Competition (50-70 mph) (s) Dynamic validation is performed using AVL Drive Quality data from CX 06 competition. Chassis Accelerometer Measurement -- installed by AVL Engine and Vehicle Speeds -- Vehicle Controller Area Network
24 Preliminary Validation Results Simulation results match well with experimental data. Longitudinal Acceleration Shifts at low gears occur more abruptly in simulation (inaccurate clutch pressure estimation) Control strategy engine start-stop feature not enabled for this test. Vehicle Speed
25 Preliminary Validation Results Engine Speed Gear shifting schedule not known precisely Other discrepancies due to differences in driver and control strategy behavior and parameter uncertainties.
26 Electric Launch: Experimental Results Further experiments performed with the engine start-stop feature: 1 st gear engaged BSA starts the engine at 10 km/h. Following that the vehicle advances to hybrid mode. Mild disturbance during engine start due to transmission and turbine speed mismatch. Electric Only Engine Start Hybrid
27 Electric Launch: Experimental Results 3 rd gear engaged BSA starts the engine at 40 km/h. Following that the vehicle advances to hybrid mode. A torque hole results in noticeable disturbance due to torque mismatch at mode transition. Shuffle during engine start. Barely noticeable by driver due to well-matched driveline speeds and low gear ratio (3 rd gear engaged). Torque Commands
28 PART 2: CONTROL
29 Hybrid Systems Definition: Hybrid systems are systems with interacting continuous and discrete-time dynamics. Why use hybrid systems approach? 1. Switching in plant dynamics 2. Need to eliminate control input discontinuities during mode changes (electric to hybrid) Other benefits of hybrid control: 1. Performance not achievable by classical techniques can be attained by switching between controllers. 2. Systems not stabilizable by continuous control (e.g. nonholonomic systems) can be stabilized by hybrid control laws.
30 Hybrid Systems and Hybrid Control Hybrid System Hybrid Controller Controller 1 Mode 1 Mode 2 Mode n Controller 2 Plant Example: Plant Controller n Examples: gain scheduling disturbance attenuation control of non-holonomic systems Hybrid Control of a Hybrid System Example: u Supervisor Controller 1 Controller 2 Mode 1 Mode 2... Mode n y Controller n
31 Modeling and Control Framework A hybrid system with m modes described by cont. diff. vector fields: switching sets: and state-transition maps:
32 Modeling and Control Framework Control Design Procedure If possible, (switching sets may be fixed by system dynamics), choose S such that Define the state-space partitions in each mode: And design controllers: to minimize the selected mode transition costs:
33 Electric Launch: Simplified HEV Driveline Why is the system hybrid? Initially engine OFF and decoupled from driveline Later, electric motors & engine are both active Mode Traversals: Clutch dynamics are discontinuous Problem essence: start engine rapidly, engage engine to driveline without causing disturbance or interrupting power output at the wheels. What is our control strategy? Prepare driveline for transition (synchronize speeds). Change control policy for different operating modes.
34 Electric Launch: Simplified HEV Driveline Switching sets are given by the nature of the system: Partitions are selected to allow for control decoupling:
35 Electric Launch: Simplified HEV Driveline Controllers * are designed to minimize mode switching costs Frequency Separation of Control Objectives * Controllers for P 10 and P 30 are designed to fulfill energy management objectives: frequency separation principle
36 Simulation Results: Electric Launch Drivability disturbance due to poor control during a mode transition from electric only to parallel hybrid. Proposed control design improves drivability during the same mode transition.
37 Simulation Results: Electric Launch Actuator torque commands are within reasonable limits. Driveline shuffle and torque sag are suppressed by better control (blue). Torque Sag Shuffle
38 Conclusions and Future Work A control-oriented dynamic model of the Ohio State Challenge-X hybrid electric vehicle is developed for drivability analysis and control development. A control approach based on the framework of hybrid systems is described to achieve smooth mode transitions. Simulation results are shown for the control of a simplified HEV driveline using the proposed approach. Current work is focused on development and implementation of a similar control strategy on the CX vehicle. Future work will focus on 1. automating the control design process 2. extending this technique for systems with model uncertainties.
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