Electronic control system for torque distribution in hybrid vehicles

• US 20040117078A1
• Filed: 10/29/2003
• Published: 06/17/2004
• Est. Priority Date: 10/29/2002
• Status: Active Grant

• Current Assignee: STMicroelectronics SRL (STMicroelectronics NV)
• Original Assignee: STMicroelectronics SRL (STMicroelectronics NV)
• Inventors: Novia, Tommaso, Rizzotto, Gianguido, Corcione, Giuseppe Esposito, Vitale, Gianluca
• Granted Patent: US 6,853,893 B2
• Time in Patent Office: Days
• US Class Current: 701/22
• CPC Class Codes: B60K 6/48 Parallel type
• CPC Class Codes: B60K 6/543 the transmission being a continuously variable transmission
• CPC Class Codes: B60L 2240/486 Operating parameters
• CPC Class Codes: B60W 10/06 including control of combustion engines
• CPC Class Codes: B60W 20/00 Control systems specially adapted for hybrid vehicles hybrid vehicle design, B60K6/00; electric vehicles B60L
• CPC Class Codes: B60W 2510/0657 Engine torque
• CPC Class Codes: B60W 2510/242 for electrical energy
• CPC Class Codes: B60W 2510/244 Charge state
• CPC Class Codes: B60W 2552/35 Road bumpiness, e.g. potholes
• CPC Class Codes: B60W 2710/105 Output torque
• CPC Class Codes: B60W 50/0097 Predicting future conditions
• CPC Class Codes: Y02T 10/40 Engine management systems
• CPC Class Codes: Y02T 10/62 Hybrid vehicles
• CPC Class Codes: Y10S 903/918 Continuously variable

Abstract

An electronic torque control and distribution system is provided for a hybrid propulsion vehicle. The drive thrust of the hybrid propulsion vehicle is distributed between an electric engine and an internal combustion engine through a transmission system. The transmission system delivers the torque of both engines to the vehicle wheels. The electronic torque control and distribution system is slaved to a control unit, and includes a controller for incorporating a fuzzy logic processor to predict through soft computing techniques the torque contributions of the electric engine and of the internal combustion engine. A sensor estimates the vehicle polluting emissions. The controller and the sensor are both connected to the control unit.

Claims

1. An electronic torque control and distribution system (11) for hybrid propulsion vehicles wherein the drive thrust is distributed between an electric engine (3) and an internal combustion engine (1) through a transmission system (2) delivering the torque of both engines (1, 3) to the vehicle wheels, being slaved to a control unit (4), characterized in that it comprises:

a controller (12) incorporating a fuzzy logic processor (13) to predict through Soft Computing techniques the torque contributions of the electric engine (3) and of the thermal engine (1);

a virtual sensor (15) for estimating the vehicle polluting emissions;

said controller (12) and said sensor (15) being connected to said control unit (4).

2. A system according to claim 1, characterized in that said controller (12) and said control unit (4) receive as input a predetermined number of operation parameters of the vehicle (10) and of the engines (1, 3) and in that it comprises respective control outputs for actuator elements of said vehicle, like the clutch or said transmission system (2), and for said engines (1, 3) supply;

the controller (12) having at the output further electric signals of torque request applied to the control unit (4).

3. A system according to claim 2, characterized in that said controller (12) receives the following inputs:

Path altimetric profile (road noise);

Driving commands (pedals);

System component status (system status);

Fuel mass capacity (ICE fuel amount);

Electric drive phase currents (ED currents);

Battery-supplied current (ESS currents);

Transmission system status (Transmission position).

4. A system according to claim 1, characterized in that the internal combustion engine (1) operates at steady state and the possible supplementary torque needed is drawn from the electric engine (3).

5. A system according to claim 1, characterized in that said controller (12) comprises a fuzzy-type processor (13) receiving as inputs at least a state-of-charge (soc) signal of the batteries (6) supplying the electric engine (3) and a signal (cycle), indicating a path calculated according to the average and the variance of the vehicle speed.

6. A system according to claim 5, characterized in that said path signal (cycle) is recalculated at predetermined time intervals (Δ

t).

7. A system according to claim 2, characterized in that said control unit (4) receives the following inputs:

Electric drive phase currents (ED currents);

Electric machine angular speed (ED speed);

Thermal machine angular speed (ICE speed);

Thermal engine timing (ICE phase);

Out-vehicle conditions (atmospheric pressure and temperature);

The torque requests outputted by the controller (12).

8. A system according to claim 5, characterized in that said processor (13) operates on membership functions according to the following fuzzy interference rules:

A) if (cycle is off) and (soc is not soc_low) then (Tice is

     0) (time is

     0)

B) if (cycle is urban) and (soc is not soc_low) then (Tice is

     0) (time is

     1)

C) if (cycle is comb) and (soc is not soc_low) then (Tice is

     50) (time is

     1)

D) if (cycle is extra) and (soc is not soc_low) then (Tice is

     50) (time is

     1)

E) if (soc is soc_low) then (Tice is

     100) (time is

     0)

9. A system according to claim 1, characterized in that said control unit (4) has a signal output defining the fuel mass capacity (ICE fuel amount) required to the internal combustion engine (3) power supply by means of said virtual sensor (15).

10. A system according to claim 1, characterized in that the prediction is performed by monitoring both the present vehicle state and the past history related to the driving conditions according to several operation data comprised in a controller memory.