Electrified Vehicles as Platforms for Complex System Control

Transcription

1 Electrified Vehicles as Platforms for Complex System Control Technical Research Department Hasan Esen HYCON2 WORKSHOP ON ENERGY

2 AGENDA 2 / DENSO Corporation Company Profile 2. Increasing Complexity of Automotive Systems 3. Example Studies 4. Outlook

3 1. DENSO Corporation Company Profile 3 / 16 global supplier of automotive technology, systems and components

4 1. DENSO Corporation Company Profile 4 / 16 global supplier of automotive technology, systems and components Established : 1949 Employees ( ) : 120,812 Subsidiaries and affiliates: Japan (80) Asia and Oceania (57) North & South America (39) Europe (36) Headquarters: Nagoya, Japan

5 1. DENSO Corporation Company Profile 5 / 16 global supplier of automotive technology, systems and components Established : 1949 Employees ( ) : 120,812 Subsidiaries and affiliates: Japan (80) Asia and Oceania (57) North & South America (39) Europe (36) Headquarters: Nagoya, Japan DENSO AUTOMOTIVE Deutschland GmbH European Technical Research Department E/E Platform & System Technologies ICT & Safety, Powertrain, E-mobility & infrastructure

6 2. Increasing Complexity of Automotive Systems 6 / 16 Vehicle System Trend: Networked & Integrated System Vehicle & Grid Integration Information & Energy Grid Integration More ECUs, larger program size, larger scale Powertrain Trend: Increasing diversity Internal Combustion Engine Electric Vehicle (EV) Efficiency Increase Biofuels Hybrid Vehicles, Plug-in Hybrids Range extender Battery electric vehicle Fuel cells Lowest Global Emission Increasing powertrain diversity

7 2. Increasing Complexity of Automotive Systems 7 / 16 Energy Flow (conventional vehicle): Engine Driving fuel Battery A/C Electric Load Mechanical Electrical Thermal refrigant Cabin Temperature coolant Heater Core (H/C) 1 function 1 component

8 2. Increasing Complexity of Automotive Systems 8 / 16 Energy Flow (hybrid, low fuel consumption vehicle): Engine Driving fuel recuperation Battery Electric Load Mechanical Exhaust heat recovery Motor / Generator refrigant A/C Elec. Heater (PTC) Cabin Temperature Electrical Thermal coolant Rankine Heater Core (H/C) 1 function multi component

9 2. Increasing Complexity of Automotive System 9 / 16 Challenging control problems today as a result of increasing complexity & scale Architectural problems High control freedom & optimality Fault-tolerance New control design concept and methodology are necessary for automotive systems DENSO Example Studies 3.1 Functional Architecture based Control System Design 3.2 Model Predictive Control for Cabin Heat Thermal Man. 3.3 Fault Tolerant Battery Control in Electrified Vehicles

10 3.1 Functional Architecture based Control System Design* 10 / 16 Aim: structuring the control system that gets larger and more complex Layer 1: Motion Domain Lateral Acceleration Motion Reference YAW Rate Longitudinal Acceleration Vehicle Speed Translation Vehicle Motion Coordinator Tire Forces Vehicle Stability Optimization Layer 2: Stability Domain Distribution Diff. Vehicle Stability Coordinator Differential Ratio Brake Torque Brake TireSteer Angle AWD Transfer Ratio AWD Steering Layer 0: Vehicle Domain Vehicle Motion Transmission Outputshaft Torque Propulsion Reference Distribution Vehicle Coordinator Transmission Outputshaft Torque Powertrain Transmission Outputshaft Torque Starter Powertrain Coordinator Starter ON/OFF Clutch Engagement Signal Clutch ElectricalEnergy, Body,Information, CabinClimate, Layer 1: Powertrain Domain Engine Torque Gear Ratio Engine Speed ISG Torque Transmission Engine ISG Main features: - Restructure vehicle control under simple rules. - Redefine and allocate all of control function appropriately - Standardize interface of each component. - Hide localized information for outside of the component. - Parallel development of each component This hierarchical structure serves as a framework. It has been gradually embodied *T. Tashiro, S. Akiyama (DENSO Corp.) Global Powertrain Conference 2003, Ann Arbor, MI, 2003

11 3.2 Model Predictive Control for Cabin Heat Thermal Man. 11 / 16 Energy Flow (hybrid, low fuel consumption vehicle): Engine Driving fuel recuperation Battery Electric Load Mechanical Exhaust heat recovery Motor / Generator refrigant A/C Elec. Heater (PTC) Cabin Temperature Electrical Thermal coolant Rankine Heater Core (H/C) distribute the workload between components to heat the cabin in order to achieve real-world (driving, electric and thermal domains) fuel efficiency

12 3.2 Model Predictive Control for Cabin Heat Thermal Man.* 12 / 16 Cabin Heat Problem Covering Range Engine Driving fuel Battery recuperation Electric Load Manipulated Observed Not included Exhaust heat recovery Motor / Generator refrigant A/C Elec. Heater (PTC) Cabin Temperature coolant Rankine Heater Core (H/C) Manipulate: Some options of engine, Electrical heater, (PTC), Heater Core (H/C) Observe/Evaluate: Battery, engine, M/G, other electrical and thermal loads * In collaboration with Prof. A. Bemporad (IMT Lucca) & his team

13 3.2 Model Predictive Control for Cabin Heat Thermal Man. 13 / 16 Control Problem y m r MPC u 1 u 2 u 3 Cabin Heat Sys. output For given measurements (y m ) and references (r), manipulate H/C (u 1 ), PTC (u 2 ), and engine power (u 3 ) to achieve the control objectives: heat power reference tracking maintaining battery SOC in its limits minimizing fuel consumption Complex relations are identified & simplified as linear-time variant (LTV) models Multi-objective MPC is formulated s.t. LTV prediction models and constraints Simulation Results (NEDC, Ambient Temp 5 o C) Heat Power [kw] Heat Power Tracking Sim Time [s] Battery SoC [%] time [s] Fuel savings w.r.t. baseline: ~ 3% Benefit: Better competitiveness

14 3.3 Fault Tolerant Battery Control in Electrified Vehicles* 14 / 16 Different Battery Topologies Type Single String Double String Multi-String fuse Complexity Sensitivity to 1-cell failure 1 parallel x n series 2 parallel x n series m parallel x n series improve the reliability of simpler topologies (single string) using active fault detection and control mechanisms * In collaboration with Prof. J. Stoustrup (Uni Aalborg) & his team. Published in Safeprocess 12 Conference

15 3.3 Fault Tolerant Battery Control in Electrified Vehicles 15 / 16 Software modifications: Active Fault Detection (AFD) 1. State space battery model Input : current I Output : voltage Vo States : voltage across bulk and surface capacitorsvcb, Vcs 2. Estimate the bulk capacity Cb and the terminal resistance Rt using Extended Kalman Filter (EKF) 3. Design the input current signal I increase the sensitivity of parameter changes Non-convex optimization problem 4. Compare the estimates with nominal values for fault detection Results Reliability of single-string topology increases with AFD Early warning to the driver, before severe failures occur

16 4. Outlook 16 / 16 Challenging control problems tomorrow as a result of increasing complexity & scale cyber-physical systems, large-scale distributed systems, systems of systems Vehicle as a component of system of systems Zero emission, zero fatality Absolute fault-tolerance Utilizing advanced computing technologies Information management Secure V2G communication Standardization DENSO EU Technical Research strategy: support and actively develop the technology together with diversified EU partners

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