Equivalent Consumption Minimization Strategy

Energy management controller for P0–P4 hybrid electric vehicles

Since R2020b

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Libraries:
Powertrain Blockset / Propulsion / Supervisory Controllers

Description

Use the Equivalent Consumption Minimization Strategy (ECMS) block to control the energy management of hybrid electric vehicles (HEVs). The block optimizes the torque split between the engine and motor to minimize energy consumption while maintaining the battery state of charge (SOC).

The HEV P0, P1, P2, P3, and P4 reference applications use the Equivalent Consumption Minimization Strategy block for hybrid control.

Use the Motor location parameter to specify the HEV motor location.

Use the ECMS method parameter to implement either an adaptive or non-adaptive ECMS method. The HEV architectures are charge-sustaining, meaning the battery SOC must remain in a specified range because there is no plugin capability to recharge the battery. The battery is an energy buffer, and all energy comes from the fuel if the change in SOC is minimized over a drive cycle. To sustain the charge over a specified drive cycle, the block implements either of these ECMS methods.

ECMS Method	Description
Non-adaptive (default)	The block uses a constant ECMS equivalence factor. Use this method to determine the best fuel economy over a drive cycle. If you change the drive cycle or HEV architecture, retune the ECMS weighting factor to maintain the ending SOC. By default, the block uses a single constant.
Adaptive	The block adjusts an ECMS equivalence factor by using the output of a PI controller. Use this method to maintain the SOC and minimize the delta SOC over many drive cycles. The block: Tunes the PI controller gains. Sustains the SOC. The PI controller minimizes the error between the target SOC and current SOC.

ECMS Control Algorithm

The block implements a dynamic supervisory controller that determines the engine torque, motor torque, starter, clutch, and brake pressure commands. Specifically, the block:

• Converts the driver accelerator pedal signal to a wheel torque request. To calculate the total powertrain torque at the wheels, the algorithm uses the maximum engine torque and motor torque curves and the transmission and differential gear ratios.

• Converts the driver brake pedal signal to a brake pressure request. The algorithm multiplies the brake pedal signal by a maximum brake pressure.

• Implements a regenerative braking algorithm for the traction motor to recover the maximum amount of kinetic energy from the vehicle.

  The block implements an ECMS algorithm^[2] that optimizes the torque split between the engine and motor to minimize energy consumption while maintaining the battery SOC. Specifically, the ECMS:

  • Assigns a cost to electrical energy, so that using stored electrical energy is equal to consuming fuel energy.

    Battery Mode	Equivalent Electrical Energy	Description
    Discharging	Positive	Battery discharges stored electrical energy when the electric machine is in use.
    Charging	Negative	Battery stores electrical energy from either the: Engine and electric machine acting as a generator Electric machine acting as a generator during regenerative braking

  • Is an instantaneous minimization method that the software solves at every controller time step. To implement the strategy, the ECMS selects the optimal motor and engine torque in the optimization strategy to minimize the equivalent energy consumption.

  • Implements either an adaptive or non-adaptive ECMS method.

Examples

Build Hybrid Electric Vehicle P0 Model

Build a vehicle using the hybrid electric vehicle (HEV) P0 reference application.

Build Hybrid Electric Vehicle P1 Model

Build a vehicle using the hybrid electric vehicle (HEV) P1 reference application.

Build Hybrid Electric Vehicle P2 Model

Build a vehicle using the hybrid electric vehicle (HEV) P2 reference application.

Build Hybrid Electric Vehicle P3 Model

Build a vehicle using the hybrid electric vehicle (HEV) P3 reference application.

Build Hybrid Electric Vehicle P4 Model

Build a vehicle using the hybrid electric vehicle (HEV) P4 reference application.

Ports

Input

WhlTrqCmd — Wheel torque command

scalar

Wheel torque command.

Data Types: double

BattSoc — Battery state of charge

scalar

Battery state of charge.

Data Types: double

BattVolt — Battery voltage

scalar

Battery voltage.

Data Types: double

Gear — Transmission gear

scalar

Transmission gear.

Data Types: double

MtrSpd — Motor speed

scalar

Motor speed.

Data Types: double

VehSpd — Vehicle speed

scalar

Vehicle speed, in m/s.

Data Types: double

TransTemp — Transmission temperature

scalar

Transmission temperature, in K.

Data Types: double

Output

Info — Block data

bus

Block data, returned as a bus signal that contains these block values.

Signal			Description	Units
EngTrqCmd			Engine torque command	N·m
MtrTrqCmd			Motor torque command	N·m
EquivFctr			Equivalence factor	NA
MinHamil			Minimum Hamiltonian	kW

EngTrqCmd — Engine torque command

scalar

Engine torque command, in N·m.

Data Types: double

MtrTrqCmd — Motor torque command

scalar

Motor torque command, in N·m.

Data Types: double

Parameters

Block Options

Motor location — Location of motor

P0 (default) | P1 | P2 | P3 | P4

Specify the HEV motor location.

ECMS method — ECMS method

Non-adaptive (default) | Adaptive

Use the ECMS method parameter to implement either an adaptive or non-adaptive ECMS method. The HEV architectures are charge-sustaining, meaning the battery SOC must remain in a specified range because there is no plugin capability to recharge the battery. The battery is an energy buffer, and all energy comes from the fuel if the change in SOC is minimized over a drive cycle. To sustain the charge over a specified drive cycle, the block implements either of these ECMS methods.

ECMS Method	Description
Non-adaptive (default)	The block uses a constant ECMS equivalence factor. Use this method to determine the best fuel economy over a drive cycle. If you change the drive cycle or HEV architecture, retune the ECMS weighting factor to maintain the ending SOC. By default, the block uses a single constant.
Adaptive	The block adjusts an ECMS equivalence factor by using the output of a PI controller. Use this method to maintain the SOC and minimize the delta SOC over many drive cycles. The block: Tunes the PI controller gains. Sustains the SOC. The PI controller minimizes the error between the target SOC and current SOC.

Differential

Differential gear ratio, N_diff — Differential gear ratio

3.32 (default) | scalar

Differential gear ratio. No dimension.

Differential efficiency factor, eta_diff — Differential efficiency factor

0.98 (default) | scalar

Differential efficiency factor. No dimension.

Loaded wheel radius, Re — Loaded wheel radius

0.327 (default) | scalar

Loaded wheel radius, in m.

Transmission

Transmission efficiency factors — Transmission efficiency factors

Gear, input torque, input speed, and temperature (default) | Gear only

Transmission efficiency factors.

Transmission gear number vector, G_trans — Transmission gear number vector

[0 1 2 3 4 5 6] (default) | vector

Transmission gear number vector. No dimension.

Transmission gear ratio vector, N_trans — Transmission gear ratio vector

[1 4.212 2.637 1.8 1.386 1 0.772] (default) | vector

Transmission gear ratio vector. No dimension.

Transmission efficiency vector, eta_trans — Transmission efficiency vector

[1 1 1 1 1 1 1] (default) | vector

Transmission efficiency vector. No dimension.

Dependencies

To enable this parameter, set Transmission efficiency factors to Gear only.

Transmission efficiency torque breakpoints, Trq_trans_bpts — Transmission efficiency torque breakpoints

[25 50 75 100 150 200 250] (default) | vector

Transmission efficiency torque breakpoints, in N·m.

Dependencies

To enable this parameter, set Transmission efficiency factors to Gear, input torque, input speed, and temperature.

Transmission efficiency speed breakpoints, omega_trans_bpts — Transmission efficiency speed breakpoints

[500.383141080919 749.619781962827 1002.676141478941 1250.957852702297 1499.239563925654 1747.521275149011 1995.802986372368 2501.915705404595 2998.479127851308 4001.155269330249 5003.83141080919] (default) | vector

Transmission efficiency speed breakpoints, in rad/s.

Dependencies

To enable this parameter, set Transmission efficiency factors to Gear, input torque, input speed, and temperature.

Transmission efficiency temperature breakpoints, Temp_trans_bpts — Transmission efficiency temperature breakpoints

[313 358] (default) | vector

Transmission efficiency temperature breakpoints, in K.

Dependencies

To enable this parameter, set Transmission efficiency factors to Gear, input torque, input speed, and temperature.

Transmission efficiency vector, eta_trans_tbl — Transmission efficiency vector

array

Transmission efficiency vector. No dimension.

Dependencies

To enable this parameter, set Transmission efficiency factors to Gear, input torque, input speed, and temperature.

Engine

Speed breakpoints, f_tbrake_n_bpt — Speed breakpoints

[0 750 1053.57142857143 1357.14285714286 1660.71428571429 1964.28571428571 2267.85714285714 2571.42857142857 2875 3178.57142857143 3482.14285714286 3785.71428571429 4089.28571428571 4392.85714285714 4696.42857142857 5000] (default) | vector

Speed breakpoints, in rpm.

Commanded torque breakpoints, f_tbrake_t_bpt — Commanded torque breakpoints

[0 15 26.4285714285714 37.8571428571429 49.2857142857143 60.7142857142857 72.1428571428571 83.5714285714286 95 106.428571428571 117.857142857143 129.285714285714 140.714285714286 152.142857142857 163.571428571429 175] (default) | vector

Commanded torque breakpoints, in N·m.

Brake torque map, f_tbrake — Brake torque map

array

Brake torque map, in N·m.

Minimum engine torque command table, f_tbrake_min — Minimum engine torque command table

vector

Minimum engine torque command table, in N·m.

Fuel flow map, f_fuel — Fuel flow map

array

Fuel flow map, in kg/s.

Minimum engine torque command, HEVEngTrq_min — Minimum engine torque command

16.18610438796213 (default) | scalar

Minimum engine torque command, in N·m.

Fuel lower heating value, LHV — Fuel lower heating value

46000000 (default) | scalar

Fuel lower heating value, in J/kg.

Engine idle speed, N_idle — Engine idle speed

750 (default) | scalar

Engine idle speed, in rpm.

Battery

Battery_state_of_charge_breakpoints__SOC_bpt____, Battery state-of-charge breakpoints, SOC_bpt — Battery state-of-charge breakpoints

[0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1] (default) | vector

Battery state-of-charge breakpoints. No dimension.

Battery charge limit table, ChrgLmt — Battery charge limit table

[1 1 1 1 1 1 1 0.9 0.7 0.5 0] (default) | vector

Battery charge limit table. No dimension.

Battery discharge limit table, DischrgLmt — Battery discharge limit table

[0 0.5 0.7 0.9 1 1 1 1 1 1 1] (default) | vector

Battery discharge limit table. No dimension.

Maximum battery current, BattCurrMax — Maximum battery current

150 (default) | scalar

Maximum battery current, in A.

DC/DC converter efficiency, eta_dcdc — DC/DC converter efficiency

1 (default) | scalar

DC/DC converter efficiency. No dimension.

Maximum battery charge power, BattChrgPwrMax — Maximum battery charge power

-30000 (default) | scalar

Maximum battery charge power, in W.

Maximum battery discharge power, BattDischrgPwrMax — Maximum battery discharge power

46000 (default) | scalar

Maximum battery discharge power, in W.

Motor

Motor maximum torque table, f_tmtr_max — Motor maximum torque table

vector

Motor maximum torque table, in N·m.

Motor speed breakpoints, f_mtr_w_bpt — Motor speed breakpoints

vector

Motor speed breakpoints, in rpm.

Motor torque breakpoints, f_mtr_t_bpt — Motor torque breakpoints

vector

Motor torque breakpoints, in N·m.

Motor efficiency map, f_mtr_eta — Motor efficiency map

array

Motor efficiency map. No dimension.

Number of motor torque calculation points, Ngrid — Number of motor torque calculation points

200 (default) | scalar

Number of motor torque calculation points. No dimension.

P0 belt ratio, N_P0 — P0 belt ratio

3 (default) | scalar

P0 belt ratio. No dimension.

Dependencies

To enable this parameter, set Motor location to P0.

Energy Management

ECMS weighting factor, ECMS_s — ECMS weighting factor

3.385 (default) | scalar

ECMS weighting factor. No dimension.

Penalty factor power, PenaltyFctrPwr — Penalty factor power

3 (default) | scalar

Penalty factor power. No dimension.

Adaptive ECMS proportional gain, ECMS_Kp — Adaptive ECMS proportional gain

0 (default) | scalar

Adaptive ECMS proportional gain. No dimension.

Dependencies

To enable this parameter, set ECMS method to Adaptive.

Adaptive ECMS integral gain, ECMS_Ki — Adaptive ECMS integral gain

0 (default) | scalar

Adaptive ECMS integral gain. No dimension.

Dependencies

To enable this parameter, set ECMS method to Adaptive.

Constraint penalty factor, PenaltyFctr — Constraint penalty factor

10000000 (default) | scalar

Constraint penalty factor. No dimension.

Target battery state-of-charge, SOCTrgt — Target battery state-of-charge

60 (default) | scalar

Target battery state-of-charge. No dimension.

Minimum battery state-of-charge, SOCmin — Minimum battery state-of-charge

40 (default) | scalar

Minimum battery state-of-charge. No dimension.

Maximum battery state-of-charge, SOCmax — Maximum battery state-of-charge

80 (default) | scalar

Maximum battery state-of-charge. No dimension.

Acknowledgments

MathWorks^® would like to acknowledge the contribution of Dr. Simona Onori to the ECMS optimal control algorithm implemented in this block. Dr. Onori is a Professor of Energy Resources Engineering at Stanford University. Her research interests include electrochemical modeling, estimation and optimization of energy storage devices for automotive and grid-level applications, hybrid and electric vehicles modeling and control, PDE modeling, and model-order reduction and estimation of emission mitigation systems. She is a senior member of IEEE^®.

References

[1] Balazs, A., Morra, E., and Pischinger, S., Optimization of Electrified Powertrains for City Cars. SAE Technical Paper 2011-01-2451. Warrendale, PA: SAE International Journal of Alternative Powertrains, 2012.

[2] Onori, S., Serrao, L., and Rizzoni, G., Hybrid Electric Vehicles Energy Management Systems. New York: Springer, 2016.

Extended Capabilities

C/C++ Code Generation
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Version History

Introduced in R2020b