EPAVersion: 2023-09-11

EST 2010 Toyota Prius 60kW 650V MG1 EMOT – ALPHA Generation Process

This document summarizes the process to generate full efficiency and power loss maps for an estimated (EST) 2010 Toyota Prius 60kW 650V MG1 electric motor and inverter (EMOT). PowerSplit hybrid vehicles use two electric motors in their drive system. One serves primarily as the drive electric motor and is called MG2 by Toyota. The other primarily serves as the generator electric motor and is called MG1 by Toyota. While the inverter voltage supplied to MG1 varies from 200 – 650 Vdc when operating in the 2010 Toyota Prius, this estimated efficiency map only focuses on MG1’s operation at 650 Vdc.

The estimated efficiency data for the MG1 map were derived using MG2 test data collected by Oak Ridge National Lab (ORNL) along with the power and voltage specifications for the MG2 motor which are detailed in NCAT’s 2010 Toyota Prius 60kW 650V MG2 EMOT - ALPHA Map Package listed in the “Related NCAT Packages.docx” file. The MG2 test data were used to inform the sizing of MG1 to provide representative operation in ALPHA’s PowerSplit model. Though similar to MG2, MG1 has a lower inertia and a constant maximum power decay profile. The generated MG1 map defines the operating boundaries and electrical power consumption of the electric motor and inverter combination which are needed for ALPHA modeling.

SUGGESTED CITATION:
EST 2010 Toyota Prius 60kW 650V MG1 EMOT - ALPHA Map Package. Version 2023-09. Ann Arbor MI: US EPA National Vehicle and Fuel Emissions Laboratory, National Center for Advanced Technology, 2023.

EMOT Physical Characteristics

The following table sets the key physical characteristics for the EST 2010 Toyota Prius 60kW 650V MG1 electric motor and inverter (EMOT) used in the ALPHA model based on published information provided in 3b- Benchmarking of Competitive Technologies Presentation by ORNL May 2011.pdf and 3c- FY2011 DOE Annual Progress Report Advanced Power Electronics and Electric Motors Program.pdf. The items in the table follow ALPHA’s code syntax for “emachines,” which is: emach.characteristic name_engineering units = value; % comments.

emach                             = class_REVS_emachine_geared;
emach.name                        = 'EST 2010 Toyota Prius 60kW 650V MG1 EMOT';
emach.type                        = enum_emachine_type.Motor;
emach.gear.ratio                  = 1; % MG1 ratio is set to 1 for this input file; the ratios for MG1 to engine and MG1 to drive axle are set elsewhere in the PS model
emach.gear.efficiency_norm        = 1; % This device is an emotor and inverter (EMOT) with no gearing, so the gear efficiency was set to 1 (100% efficiency)
emach.inertia_kgm2                = 3.93 * (1/2*0.1513*1/2)^2;  % Inertia = rotor mass *1/2 rotor diameter,  rotor mass = 3.93kg, rotor diameter = 0.1513m.  (0.0056 kg-m2) for the MG1
emach.max_speed_radps             = 13500 * unit_convert.rpm2radps;
emach.max_torque_Nm               = 207;
emach.max_motor_power_W           = 60000; % Using MG2 max power
emach.max_generator_power_W       = emach.max_motor_power_W;
nominalVoltage_V                  = 650; % Using MG2 voltage

Import EMOT Data

The following code imports EMOT efficiency data provided by ORNL found in 3c- 2010 Toyota Prius 60kW 650V MG2 EMOT - ORNL Test Data File.xlsx detailed in NCAT’s 2010 Toyota Prius 60kW 650V MG2 EMOT - ALPHA Map Package. ORNL provided separate motor and inverter efficiency data files which were multiplied together to provide the combined efficiency data used to create the MG2 EMOT map.

EPA reviews the quality of the test data we import to ensure consistency with expected data trends and emotor system physics. Any data points considered significant outliers are removed from the dataset before generating the final efficiency map. In addition, since many of the datasets are missing low-speed and torque datapoints, occasionally a few “grounding” datapoints are added to help the curve fitting algorithm extrapolate the gradients near the map’s boundaries.

Specifically for this dataset, the efficiency datapoints associated with 0.0 torque were removed since the values associated with those datapoints did not make sense physically.

tbl_inv                 = readmatrix('3c- 2010 Toyota Prius 60kW 650V MG2 EMOT - ORNL Test Data File.xlsx','Sheet','650V INV Only', 'Range','B6:P27');
tbl_mot                 = readmatrix('3c- 2010 Toyota Prius 60kW 650V MG2 EMOT - ORNL Test Data File.xlsx','Sheet','650V Motor Only', 'Range','B6:P27');
data(1).speed_rpm       = tbl_mot(1,2:end);
data(1).torque_Nm       = tbl_mot(3:end,1);
data(1).efficiency_norm = tbl_mot(3:end,2:end)/100 .* tbl_inv(3:end,2:end)/100;
data(1).name            = 'Data';

EMOT Torque Limits

The torque limits for the EST 2010 Toyota Prius 60kW 650V MG1 EMOT were set to follow a constant decay profile which is automatically applied in the ALPHA build process. The secondary axis information is provided below to keep the build process consistent across other emachines.

emach.positive_torque_limit_Nm.axis_2.signal        = 'emach_voltage_V';
emach.positive_torque_limit_Nm.axis_2.breakpoints   = nominalVoltage_V;

Build the emachine Object in Matlab

The script below creates an “emach” object which is converted into power loss (rather than efficiency) for the “drive” quadrant, extrapolated to the edges of the operating space, and scaled for maximum power.

These power losses were then “mirrored” to the regen quadrant considering the average of the empirical internal mechanical and electrical losses differences typically seen between operating in the “drive” and “regen” quadrants. Since the ORNL dataset did not have any regen data, we mirrored the drive quadrant power loss data onto the regen quadrant compensated by a factor of 1.05 (or 105 %) which represents an empirical average encountered in confidential data available to this program.

emach = emach.load_data(data,'mirror_factor',1.05,'use_cluster_breakpoints');

EMOT Efficiency Map

The following code generates the Efficiency Map shown below. The efficiency data points used to generate the efficiency map are superimposed on this image. A clean version of the efficiency map (without data points) is included in 4a- EST 2010 Toyota Prius 60kW 650V MG1 EMOT – Efficiency.pdf. The 6- EST 2010 Toyota Prius 60kW 650V MG1 EMOT - Electrical Power Consumption Data.xlsx file contains a sample data set extracted from this efficiency map.

This data set also includes data in the negative speed quadrants (not shown in the figure). These data are created by rotating the positive speed quadrants, such that losses in the third quadrant (negative speed and negative torque) match losses in the first quadrant (positive speed and positive torque), and losses in the fourth quadrant (negative speed and positive torque) match losses in the second quadrant (positive speed and negative torque).

REVS_plot_emachine(emach,'efficiency');
REVS_plot_emachine_data_overlay(data, 'efficiency');

For comparison, the Combined Inverter-Motor Efficiency Map shown below was published by ORNL in a technical presentation provided in 3b- Benchmarking of Competitive Technologies Presentation by ORNL May 2011.pdf and 3c- FY2011 DOE Annual Progress Report Advanced Power Electronics and Electric Motors Program.pdf.

Power Loss Difference Table

In addition, the diagram below shows the power loss difference by comparing the power loss data derived from the ORNL efficiency data found in 3c- 2010 Toyota Prius 60kW 650V MG2 EMOT - ORNL Test Data File.xlsx and the ALPHA map power data. The power loss percentage difference for these data points is calculated using the following formula.

$$\delta P_{loss} = \frac{P_{loss}(map) - P_{loss}(data)}{P_{loss}(data)}$$

Where

$$P_{loss} = | P_{mech} - P_{elec} |$$

In cases where the original ORNL data contain abrupt changes in curvature, the ALPHA curve-fitting function produces a smooth surface through the points, resulting in a noticeable difference between the values of the original ORNL points and the curve fit surface. Additionally, larger percentage values for power loss difference are typical where the magnitude of the power loss is small (for example, at low torques and speeds).

REVS_table_data_comparision_emachine(data,emach, 'loss_diff_pct');
                                                                                            Data Power Loss Percent Difference
                                                                                            ----------------------------------

                                                                                      Motor Torque ( Nm ) \ Motor Speed ( RPM)

                   500 RPM      1000 RPM      2000 RPM      3000 RPM      4000 RPM      5000 RPM      6000 RPM      7000 RPM      8000 RPM      9000 RPM     10000 RPM     11000 RPM     12000 RPM     13000 RPM
                __________    __________    __________    __________    __________    __________    __________    __________    __________    __________    __________    __________    __________    __________

    200.0 Nm      -3.71          1.62          1.36           NaN           NaN           NaN           NaN           NaN           NaN           NaN           NaN           NaN           NaN           NaN   
    190.0 Nm       8.01         -3.19         -3.11           NaN           NaN           NaN           NaN           NaN           NaN           NaN           NaN           NaN           NaN           NaN   
    180.0 Nm      -3.17          2.37          1.72          0.95           NaN           NaN           NaN           NaN           NaN           NaN           NaN           NaN           NaN           NaN   
    170.0 Nm      -0.33         -1.36         -0.64         -1.43           NaN           NaN           NaN           NaN           NaN           NaN           NaN           NaN           NaN           NaN   
    160.0 Nm       4.46          0.99          0.38          0.82           NaN           NaN           NaN           NaN           NaN           NaN           NaN           NaN           NaN           NaN   
    150.0 Nm       -5.2         -0.48          0.32          0.23           NaN           NaN           NaN           NaN           NaN           NaN           NaN           NaN           NaN           NaN   
    140.0 Nm      -0.65          1.91          0.42          -0.6          0.08           NaN           NaN           NaN           NaN           NaN           NaN           NaN           NaN           NaN   
    130.0 Nm       5.08         -2.26         -1.13          1.31         -0.74           NaN           NaN           NaN           NaN           NaN           NaN           NaN           NaN           NaN   
    120.0 Nm      -4.04          1.44          1.45         -1.45          0.84           NaN           NaN           NaN           NaN           NaN           NaN           NaN           NaN           NaN   
    110.0 Nm      -0.27          0.41         -1.46          0.41          0.36           NaN           NaN           NaN           NaN           NaN           NaN           NaN           NaN           NaN   
    100.0 Nm       1.04         -0.22          0.36         -0.19          0.68          -1.2           NaN           NaN           NaN           NaN           NaN           NaN           NaN           NaN   
    90.0 Nm        0.66         -0.16          1.89          0.07         -0.54          1.85           NaN           NaN           NaN           NaN           NaN           NaN           NaN           NaN   
    80.0 Nm        0.28         -0.22         -3.71           0.5         -0.58           0.7         -2.74           NaN           NaN           NaN           NaN           NaN           NaN           NaN   
    70.0 Nm       -0.07          0.23          2.21         -0.44          0.38          0.43          3.18           NaN           NaN           NaN           NaN           NaN           NaN           NaN   
    60.0 Nm       -0.12         -0.06          0.51             0         -0.49         -0.92          0.58          -0.7           NaN           NaN           NaN           NaN           NaN           NaN   
    50.0 Nm       -0.42          0.32         -0.36          0.47         -0.28          1.06            -1          1.87         -1.08           NaN           NaN           NaN           NaN           NaN   
    40.0 Nm       -0.56          0.22         -0.12         -0.56          0.25           1.8         -0.62         -0.09          1.73         -0.38         -2.19           NaN           NaN           NaN   
    30.0 Nm       -0.66         -0.18         -0.83         -0.22          -0.3         -2.74          1.32         -0.34          -0.8          0.47          2.88         -3.06         -0.78           NaN   
    20.0 Nm       -1.37         -1.19         -1.24         -1.62         -2.77         -1.64            -1         -0.73           0.8         -0.65          1.21          4.92          1.04         -2.51   
    10.0 Nm        3.63           1.4          2.64          2.61          3.23           3.3         -0.25          1.33         -0.21          1.09         -0.36          -0.3          0.91           2.9   

Power Loss Map

The Power Loss map is shown below and in 5a- EST 2010 Toyota Prius 60kW 650V MG1 EMOT - Power Loss.pdf. Following this are two graphs expressing losses in the EMOT as “effective torque loss” as functions of motor output torque and speed. The additional plots show system losses, converted to effective torque loss, as a function of motor output torque and speed. Effective torque loss represents the total power loss in the system as a loss of mechanical power. The associated speed is kept constant, and thus the total loss is expressed as a loss of torque. Torque losses are presented on a log scale.

REVS_plot_emachine(emach,'power loss');
REVS_plot_emachine(emach,'torque loss curves');

Generate ALPHA .m file for ALPHA Model Simulations

This code generates and writes the created ALPHA emachine definition into an “.m file” for use in later ALPHA vehicle model simulations. The .m file is the actual input file used in ALPHA that defines power consumption over the speed and torque operating limits of the EST 2010 Toyota Prius 60kW 650V MG1 EMOT.

emach.write_mscript('emachine_est_2010_Toyota_Prius_60kW_650V_MG1_EMOT.m');

Motor Build: emachine_est_2010_Toyota_Prius_60kW_650V_MG1_EMOT.m


% ALPHA ELECTRIC MOTOR DEFINITION
% Generated 11-Sep-2023 15:07:09

% Constructor
mg = class_REVS_emachine_geared();
mg.name =  'EST 2010 Toyota Prius 60kW 650V MG1 EMOT'; 
mg.source_filename = mfilename;

% Physical Description
mg.electrical_source =  'propulsion'; 
mg.inertia_kgm2 =  0.0056227713562499995; 
mg.type = enum_emachine_type.Motor;
mg.gear.ratio =  1; 
mg.gear.efficiency_norm =  1; 

% Capacity Limits
mg.max_speed_radps =  1413.7166941154069; 
mg.max_torque_Nm =  207; 
mg.max_motor_power_W =  60000; 
mg.max_generator_power_W =  60000; 
mg.positive_torque_limit_Nm = class_REVS_dynamic_lookup;
mg.positive_torque_limit_Nm.axis_1.signal =  'emach_spd_radps'; 
mg.positive_torque_limit_Nm.axis_1.breakpoints = [	    -1427.8538610565611	   -1413.7166941154069	   -1327.0473197136373	   -1071.4487114419444	   -898.40887060548050	   -773.48965966454955	   -679.06860379921011	   -605.19190953973566	   -545.81232674049500	   -497.04389682415115	   -456.27559045663583	   -421.68808398251099	   -391.97483108979321	   -366.17329633055812	   -343.55872593958787	   -323.57499276213832	   -305.78824968415296	   -289.85507246376812	    0.0000000000000000	    289.85507246376812	    305.78824968415296	    323.57499276213832	    343.55872593958787	    366.17329633055812	    391.97483108979321	    421.68808398251099	    456.27559045663583	    497.04389682415115	    545.81232674049500	    605.19190953973566	    679.06860379921011	    773.48965966454955	    898.40887060548050	    1071.4487114419444	    1327.0473197136373	    1413.7166941154069	    1427.8538610565611		]; 
mg.positive_torque_limit_Nm.axis_2.signal =  'emach_voltage_V'; 
mg.positive_torque_limit_Nm.axis_2.breakpoints =  650; 
mg.positive_torque_limit_Nm.table = [	     0.0000000000000000	    42.441318157838758	    45.213157894736838	    55.998947368421057	    66.784736842105247	    77.570526315789493	    88.356315789473683	    99.142105263157887	    109.92789473684211	    120.71368421052631	    131.49947368421053	    142.28526315789475	    153.07105263157894	    163.85684210526315	    174.64263157894737	    185.42842105263156	    196.21421052631578	    207.00000000000000	    207.00000000000000	    207.00000000000000	    196.21421052631578	    185.42842105263156	    174.64263157894737	    163.85684210526315	    153.07105263157894	    142.28526315789475	    131.49947368421053	    120.71368421052631	    109.92789473684211	    99.142105263157887	    88.356315789473683	    77.570526315789493	    66.784736842105247	    55.998947368421057	    45.213157894736838	    42.441318157838758	    0.0000000000000000		]; 

% Losses & Efficiency
mg.electric_power_W = class_REVS_dynamic_lookup;
mg.electric_power_W.axis_1.signal =  'emach_spd_radps'; 
mg.electric_power_W.axis_1.breakpoints = [	    -1361.3568165555769	   -1256.6370614359173	   -1151.9173063162575	   -1047.1975511965977	   -942.47779607693792	   -837.75804095727813	   -733.03828583761833	   -628.31853071795865	   -523.59877559829886	   -418.87902047863895	   -314.15926535897938	   -209.43951023931945	   -104.71975511965972	    0.0000000000000000	    104.71975511965972	    209.43951023931945	    314.15926535897938	    418.87902047863895	    523.59877559829886	    628.31853071795865	    733.03828583761833	    837.75804095727813	    942.47779607693792	    1047.1975511965977	    1151.9173063162575	    1256.6370614359173	    1361.3568165555769		]; 
mg.electric_power_W.axis_2.signal =  'emach_trq_Nm'; 
mg.electric_power_W.axis_2.breakpoints = [	    -200.00000000000000	   -190.00000000000000	   -180.00000000000000	   -170.00000000000000	   -160.00000000000000	   -150.00000000000000	   -140.00000000000000	   -130.00000000000000	   -120.00000000000000	   -110.00000000000000	   -100.00000000000000	   -90.000000000000000	   -80.000000000000000	   -70.000000000000000	   -60.000000000000000	   -50.000000000000000	   -40.000000000000000	   -30.000000000000000	   -15.000000000000000	    0.0000000000000000	    10.000000000000000	    20.000000000000000	    30.000000000000000	    40.000000000000000	    50.000000000000000	    60.000000000000000	    70.000000000000000	    80.000000000000000	    90.000000000000000	    100.00000000000000	    110.00000000000000	    120.00000000000000	    130.00000000000000	    140.00000000000000	    150.00000000000000	    160.00000000000000	    170.00000000000000	    180.00000000000000	    200.00000000000000		]; 
mg.electric_power_W.table = [
    289089.20593803411	    260287.68783703394	    245886.31198532184	    231484.57587825140	    217082.54817290459	    202680.56167363506	    188279.32644923098	    173880.03978661777	    159484.47853237166	    145095.04933546839	    130714.76013857922	    116347.06331261322	    101995.51016254206	    87663.153996351743	    73351.654416933117	    59060.084088232368	    44783.541872393711	    30511.858398142849	    16228.966647891046	    2352.7841194099710	   -17433.266760237842	   -36523.088716737955	   -49298.482510351438	   -62085.820574877558	   -74872.905184812276	   -87653.174701753887	   -100424.05205419019	   -113185.47773423072	   -125938.76428721282	   -138685.78716448147	   -151428.46748799764	   -164168.48122536647	   -176907.12919196757	   -189645.31203781351	   -202383.56736759766	   -215122.13888651165	   -227861.05836378795	   -240600.22972962281	   -253339.51076458493	;
    267071.12992103695	    240479.53555049002	    227184.35500592654	    213889.54644239575	    200595.07026634066	    187300.64536337255	    174005.64257961366	    160708.98658470347	    147409.08963676987	    134103.85948612355	    120790.84918339782	    107467.64791292706	    94132.644426698243	    80786.316585251174	    67433.188967374997	    54084.515795723171	    40761.527024509916	    27498.636512627516	    14470.750115211407	    1736.0744463647693	   -16743.859404853905	   -34472.073689135505	   -46173.083097492199	   -57841.921502006597	   -69505.448682601753	   -81178.224905628260	   -92866.472480387369	   -104571.30585508735	   -116291.08559325122	   -128022.98520477637	   -139763.94363908953	   -151511.18184635401	   -163262.43353441067	   -175016.00268083991	   -186770.72532398478	   -198525.88506447474	   -210281.11115574016	   -222036.27401571421	   -233791.38399349677	;
    245067.42641398858	    220666.04124637228	    208466.16831732768	    196266.81915756915	    184068.03331661716	    171869.64052855870	    159671.18747595130	    147471.89381470025	    135270.65052737662	    123066.06795837868	    110856.56423984913	    98640.451281974005	    86415.919262234529	    74180.739383235123	    61931.406837647861	    49661.361815723554	    37357.925214803807	    24997.794168962806	    13000.962757487947	    1302.4806849416564	   -15648.283778590583	   -31609.501602426626	   -42301.167821370691	   -53007.035862185410	   -63720.180059329774	   -74439.289430266435	   -85165.022698057786	   -95898.109002940982	   -106638.61798811246	   -117385.88954246900	   -128138.75735216393	   -138895.84284735634	   -149655.80593768487	   -160417.51092028560	   -171180.10637639835	   -181943.03613694379	   -192706.00308690296	   -203468.90515502513	   -214231.75758093849	;
    223078.09915685249	    200845.96417872392	    189729.94139404796	    178614.02146955294	    167498.37286612298	    156383.24363978853	    145268.92014552478	    134155.62338740777	    123043.30394730142	    111931.28418064433	    100817.69057448581	    89698.633279495451	    78567.146077035766	    67412.028294918942	    56216.960077877389	    44960.603857572503	    33618.812739396220	    22527.677995015136	    11715.442187846134	    1120.5782258726379	   -14343.052244836517	   -29118.605369709290	   -38651.826369982577	   -48279.874562840509	   -57973.585359033903	   -67707.980651765436	   -77464.598237459402	   -87231.333799046595	   -97001.168008627705	   -106770.63655450258	   -116538.47964976296	   -126304.62749214956	   -136069.52384799221	   -145833.72404537647	   -155597.68929771410	   -165361.70906746085	   -175125.90045019763	   -184890.25008284434	   -194654.67698513149	;
    201084.05254929553	    181020.44043219136	    170986.43915251645	    160950.78156690139	    150912.70456131763	    140871.44239752894	    130826.26349266036	    120776.46425887659	    110721.34755548020	    100660.25576074426	    90592.778053136601	    80519.286465279394	    70441.935618061238	    60366.129446819468	    50302.155106334772	    40266.205949805590	    30279.465463232274	    20412.883754535243	    10680.960306662504	    1144.1883231888901	   -12733.418145931038	   -26173.309659778737	   -34996.749310969280	   -43770.406326854798	   -52515.612023864982	   -61248.527170280526	   -69979.247905748562	   -78712.947149103318	   -87451.621396442366	   -96195.619271929492	   -104944.64668856503	   -113698.26746206296	   -122456.05536270345	   -131217.57017239393	   -139982.28907379266	   -148749.56899808918	   -157518.66860137932	   -166288.82836238126	   -175059.39302718613	;
    179065.14930323500	    161182.94548294871	    152237.46440137632	    143288.38148217986	    134333.62811321934	    125371.07704067809	    116398.99624583389	    107416.57970038698	    98424.474900058587	    89425.158500059959	    80422.957243872515	    71423.518035766116	    62432.683883935417	    53455.134315578180	    44493.877551521582	    35547.982717520383	    26757.857396337015	    18081.969551575647	    9546.5038106430165	    1121.2957961544753	   -11312.533520664139	   -23432.065168875837	   -31368.644579743086	   -39149.615374776324	   -46912.965522316459	   -54658.484865818027	   -62389.820749705177	   -70112.145492199124	   -77831.702714398329	   -85554.451791458603	   -93284.943055572498	   -101025.79634044869	   -108777.73721801012	   -116539.98681068476	   -124310.79466728077	   -132087.96065300400	   -139869.26307240894	   -147652.77046916573	   -155437.05421917560	;
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   -194654.67698513149	   -184890.25008284434	   -175125.90045019763	   -165361.70906746085	   -155597.68929771410	   -145833.72404537647	   -136069.52384799221	   -126304.62749214956	   -116538.47964976296	   -106770.63655450258	   -97001.168008627705	   -87231.333799046595	   -77464.598237459402	   -67707.980651765436	   -57973.585359033903	   -48279.874562840509	   -38651.826369982577	   -29118.605369709290	   -14343.052244836517	    1120.5782258726379	    11715.442187846134	    22527.677995015136	    33618.812739396220	    44960.603857572503	    56216.960077877389	    67412.028294918942	    78567.146077035766	    89698.633279495451	    100817.69057448581	    111931.28418064433	    123043.30394730142	    134155.62338740777	    145268.92014552478	    156383.24363978853	    167498.37286612298	    178614.02146955294	    189729.94139404796	    200845.96417872392	    223078.09915685249	;
   -214231.75758093849	   -203468.90515502513	   -192706.00308690296	   -181943.03613694379	   -171180.10637639835	   -160417.51092028560	   -149655.80593768487	   -138895.84284735634	   -128138.75735216393	   -117385.88954246900	   -106638.61798811246	   -95898.109002940982	   -85165.022698057786	   -74439.289430266435	   -63720.180059329774	   -53007.035862185410	   -42301.167821370691	   -31609.501602426626	   -15648.283778590583	    1302.4806849416564	    13000.962757487947	    24997.794168962806	    37357.925214803807	    49661.361815723554	    61931.406837647861	    74180.739383235123	    86415.919262234529	    98640.451281974005	    110856.56423984913	    123066.06795837868	    135270.65052737662	    147471.89381470025	    159671.18747595130	    171869.64052855870	    184068.03331661716	    196266.81915756915	    208466.16831732768	    220666.04124637228	    245067.42641398858	;
   -233791.38399349677	   -222036.27401571421	   -210281.11115574016	   -198525.88506447474	   -186770.72532398478	   -175016.00268083991	   -163262.43353441067	   -151511.18184635401	   -139763.94363908953	   -128022.98520477637	   -116291.08559325122	   -104571.30585508735	   -92866.472480387369	   -81178.224905628260	   -69505.448682601753	   -57841.921502006597	   -46173.083097492199	   -34472.073689135505	   -16743.859404853905	    1736.0744463647693	    14470.750115211407	    27498.636512627516	    40761.527024509916	    54084.515795723171	    67433.188967374997	    80786.316585251174	    94132.644426698243	    107467.64791292706	    120790.84918339782	    134103.85948612355	    147409.08963676987	    160708.98658470347	    174005.64257961366	    187300.64536337255	    200595.07026634066	    213889.54644239575	    227184.35500592654	    240479.53555049002	    267071.12992103695	;
   -253339.51076458493	   -240600.22972962281	   -227861.05836378795	   -215122.13888651165	   -202383.56736759766	   -189645.31203781351	   -176907.12919196757	   -164168.48122536647	   -151428.46748799764	   -138685.78716448147	   -125938.76428721282	   -113185.47773423072	   -100424.05205419019	   -87653.174701753887	   -74872.905184812276	   -62085.820574877558	   -49298.482510351438	   -36523.088716737955	   -17433.266760237842	    2352.7841194099710	    16228.966647891046	    30511.858398142849	    44783.541872393711	    59060.084088232368	    73351.654416933117	    87663.153996351743	    101995.51016254206	    116347.06331261322	    130714.76013857922	    145095.04933546839	    159484.47853237166	    173880.03978661777	    188279.32644923098	    202680.56167363506	    217082.54817290459	    231484.57587825140	    245886.31198532184	    260287.68783703394	    289089.20593803411	]; 
mg.unpowered_torque_loss_Nm = class_REVS_dynamic_lookup;
mg.unpowered_torque_loss_Nm.axis_1.signal =  'emach_spd_radps'; 
mg.unpowered_torque_loss_Nm.axis_1.breakpoints = [	    -15000.000000000000	    15000.000000000000		]; 
mg.unpowered_torque_loss_Nm.table = [	     0.0000000000000000	    0.0000000000000000		];